Relevant bibliographies by topics / Objects of a crime classification

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Objects of a crime classification'

Author: Grafiati
Published: 4 June 2025
Last updated: 23 June 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Objects of a crime classification.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Objects of a crime classification"

1

Panchenko, O. H. "CLASSIFICATION OF CRIME OBJECTS IN THE CONCEPTUAL POSITIONS OF THE THEORY OF STATE AND LAW." Actual problems of native jurisprudence, no. 4 (August 30, 2019): 22–25. http://dx.doi.org/10.15421/391905.

Full text
Abstract:
The article examines the specifics of the philosophical and legal classification of crime in the conceptual positions of the theory of state and law. The categorical classification of the objects of the crime system as structured vertically and structured horizontally, which allowed distribution of crimes directly, kind, generic, general, was analyzed. It is shown that the general object of the crime is traditionally in the conceptual positions of the theory of state and law called the whole set of social relations, which are protected by criminal law. The generic object of the crime is a certain circle of homogeneous economic, social, political content of social relations, which, for some reason, should be protected by a single set of legal norms. It is made general that the specific object of a crime is a set of social relations within the generic object, which reflect the same interest of the participants in such relations or express though the nonidentical, but closely interrelated interests. The direct object of the crime is those specifically social relations, set by the legislator under the protection of a certain legal norm. It is shown that structured horizontal objects of crime are distributed directly to the main and directly additional. It is traced that under the direct object of the crime is understood those social relations, the violation of which is the social content of the crime and for the protection of which there is a legal norm, which implies responsibility for the commission of the crime. Under the direct additional object of the crime are those social relations, the encroachment on which does not constitute the content of the crime, but the commission of such a crime is always caused damage. It is concluded that the study of the concept of crime within the conceptual concepts of the theory of state and law is justified by the subject of its study. The fundamental questions in this context arose the problem of what exactly is the legal facts, which, depending on the result, can be classified categorically into legal, lawful, and law-stopping. It is proved that the most important is the distribution of legal facts by their individual connection with the participants in the legal relationship. Thus, according to the categorical regularity of concepts of the theory of state and law, wrongful actions are divided, first, into offenses, that is, crimes and misdemeanors; and secondly, on objectively unlawful acts.
APA, Harvard, Vancouver, ISO, and other styles
2

Popovich, O. "Object of a terrorist act: the generic object of the crime." Analytical and Comparative Jurisprudence, no. 4 (April 28, 2022): 308–12. http://dx.doi.org/10.24144/2788-6018.2021.04.53.

Full text
Abstract:
The article is devoted to the problematic issues of establishing the generic object of a terrorist act. The object of a terrorist act is important to establish the public danger of the act and its consequences, the recognition of the act as a crime, the qualification of this act and the prosecution. Attention is paid to different views of the nature and types of the object of the crime. The three-level classification according to the level of generalization of objects of crime "vertically" is considered - according to the level of generalization of objects of crime "vertically" (general, generic with definition if necessary within its limits and species object, ), and "horizontally" at the level of the direct object of the crime - the main direct and additional direct objects of the crime. Scholars also use the classification at the level of additional direct object of crime with the division of this object into two types - additional mandatory (required) and additional optional, and at the level of direct object of crime "horizontally". The special significance of the generic object of a criminal offense (criminal misdemeanor or crime) in the considered classification of objects "vertically" is emphasized. The generic (group) object of a criminal offense is a certain range of identical or homogeneous in its social and economic essence of social relations, which as a result are protected by a single set of interrelated criminal law. It has been proven that the controversial issue of the generic object of a terrorist act has a negative impact on judicial practice, because there is a lack of certainty that all the defining, typical features of the crime are clearly defined. As noted in legal scientific publications, the correctness of fixing the signs of the crime and the choice of their location in the relevant article of the Special Part of the Criminal Code serves as a legal basis for ensuring rights and freedoms in criminal proceedings. In addition, without an accurate description of the signs of a criminal offense in the rules establishing criminal liability for criminal (criminal illegal) acts, as well as without a full solution to other issues of criminal remedies to combat these crimes (criminal offenses) proper implementation of constitutional and international The principle of the rule of law is impossible, which is one of the key indicators of Ukraine's development as a legal and democratic state, which is on the path to European integration.
 The defining characteristics of a terrorist act have been established, such as: a generally dangerous act, aimed at spreading fear and terror among the population or a particular social group, the ultimate goal of a terrorist attack, which is to unlawfully (illegally) influence other legal or natural persons. their behavior, which is desirable for the subject of the crime. The generic object of the terrorist act has been identified.
APA, Harvard, Vancouver, ISO, and other styles
3

Golubev, Filipp Alekseevich. "Criminalistic characteristic of investigation of undue influence upon critical information structure of the Russian Federation." Право и политика, no. 10 (October 2020): 50–59. http://dx.doi.org/10.7256/2454-0706.2020.10.33985.

Full text
Abstract:
This article provides comprehensive description of the crime established by the Article 274.1 of the Criminal Code of the Russian Federation. The subject of this research is the crimes in the area of information technologies and their circumstances set by the Article 274.1 of the Criminal Code of the Russian Federation, as well as comprehensive characteristic of criminal impact upon the critical information infrastructure of the Russian Federation. The subject of research also includes the concept of the object of infringement – the critical information structure of the Russian Federation, isolated circumstances of the instance of crime that determine the nature and dynamics of criminal activity thereof, classification and criminalistic characteristic of the objects of crime, essential evidence of unfavorable consequences of undue influence upon critical information structure of the Russian Federation. Definition is given to the concept of the object of infringement – the critical information structure of the Russian Federation. The author examines isolated circumstances the instance of crime that determine the nature and dynamics of criminal activity thereof. Classification and criminalistic characteristic are given to the objects of crime; essential evidence of unfavorable consequences of undue influence upon the critical information structure of the Russian Federation is identified and analyzed. The author concludes that taking into consideration the fact that currently there is no practice, guidelines, recommendations on investigation and detection of crimes established by the Article 274.1 of the Criminal Code of the Russian Federation, the crimes that fall under the indicated category have even grater latency compared to other crimes of the Chapter 28 of the Criminal Code of the Russian Federation, which necessitates the development of guidelines, recommendations, normative legal and local acts on detection, investigation and prevention of crimes in the area of computer technologies.
APA, Harvard, Vancouver, ISO, and other styles
4

Ermashev, Jengis. "OBJECTIVE SIGNS OF SMUGGLING." CRIMINOLOGY AND CRIMINAL JUSTICE 3, no. 3 (2023): 4–13. http://dx.doi.org/10.51788/tsul.ccj.3.3./xeai2412.

Full text
Abstract:
This article examines in detail the objective features of the crime of smuggling as a type of crime against public safety, that is, the object and objective sides of this act. In particular, in this article, when analyzing the object of smuggling, various arguments are considered regarding its general, special, similar, and direct objects (vertical classification), as well as directly basic, directly additional, and directly optional objects (horizontal classification). The author’s conclusions are analyzed and formulated. The article also pays attention to the problem of contraband and proposes a classification and analysis of contraband provided for by national criminal legislation, dividing it into two types. This article, paying attention to the objective side of smuggling, indicates that this crime is committed by evading customs control, hiding from customs control, using fraudulently produced customs documents or documents without declaration, or using a declaration written in another name. At the same time, the opinions of scientists regarding the content of each act, representing the objective side of this crime, the explanations of the Plenum of the Supreme Court of the Republic of Uzbekistan were carefully analyzed, and the author’s conclusions on each case were presented.
APA, Harvard, Vancouver, ISO, and other styles
5

Abdul Islam, Abdul Kalam, Y Veeranjaneyulu, G N V Bhavana, and S. Sriramana Swamy. "FOREINSICS IMAGE DETECTION AND CLASSIFICATION USING YOLO." Journal of Nonlinear Analysis and Optimization 15, no. 02 (2024): 889–93. https://doi.org/10.36893/jnao.2024.v15i2.139.

Full text
Abstract:
In the realm of digital forensics, the accurate and efficient analysis of images is crucialfor the investigation and solving of crimes. This project presents a forensic image classification and detection methodology using the "You Only Look Once" (YOLO) algorithm, a state-of-the-art object detection model. YOLO's real-time detection capabilities and high accuracy make it a potent tool for forensic applications, where timely and precise identification of elements within an image can be critical.The research involves training the YOLO model on a comprehensive dataset of forensic images, encompassing various scenarios such as crime scenes, digital evidence, and suspicious activities. By leveraging YOLO's deep learning architecture, the model can accurately classify and detect objects and scenes.
APA, Harvard, Vancouver, ISO, and other styles
6

Srikanth, H. S. Tanvi. "Crime Pattern Analysis, Visualization and Pridiction Using Data Mining." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (2021): 397–401. http://dx.doi.org/10.22214/ijraset.2021.37323.

Full text
Abstract:
Crime against women these days has become problem of every nation around the globe many countries are trying to curb this problem. Preventive are taken to reduce the increasing number of cases of crime against women. A huge amount of data set is generated every year on the basis of reporting of crime. This data can prove very useful in analyzing and predicting crime and help us prevent the crime to some extent. Crime analysis is an area of vital importance in police department. Study of crime data can help us analyze crime pattern, inter-related clues& important hidden relations between the crimes. That is why data mining can be great aid to analyze, visualize and predict crime using crime data set. Classification and correlation of data set makes it easy to understand similarities & dissimilarities amongst the data objects. We group data objects using clustering technique. Dataset is classified on the basis of some predefined condition. Here grouping is done according to various types of crimes against women taking place in different states and cities of India. Crime mapping will help the administration to plan strategies for prevention of crime, further using data mining technique data can be predicted and visualized in various form in order to provide better understanding of crime patterns.
APA, Harvard, Vancouver, ISO, and other styles
7

Swadi Al-Janabi, Kadhim B. "A Proposed Framework for Analyzing Crime Data Set Using Decision Tree and Simple K-Means Mining Algorithms." Journal of Kufa for Mathematics and Computer 1, no. 3 (2011): 8–24. http://dx.doi.org/10.31642/jokmc/2018/010302.

Full text
Abstract:
This paper presents a proposed framework for the crime and criminal data analysis and detection using Decision tree Algorithms for data classification and Simple K Means algorithm for data clustering. The paper tends to help specialists in discovering patterns and trends, making forecasts, finding relationships and possible explanations, mapping criminal networks and identifying possible suspects. The classification is based mainly on grouping the crimes according to the type, location, time and other attributes; Clustering is based on finding relationships between different Crime and Criminal attributes having some previously unknown common characteristics. The results of both classifications and Clustering are used for prediction of trends and behavior of the given objects (Crimes and Criminals).Data for both crimes and criminals were collected from free police departments’ dataset available on the Internet to create and test the proposed framework, and then these data were preprocessed to get clean and accurate data using different preprocessingtechniques (cleaning, missing values and removing inconsistency). The preprocessed data were used to find out different crime and criminal trends and behaviors, and crimes and criminals were grouped into clusters according to their important attributes. WEKA mining software and Microsoft Excel were used to analyze the given data.
APA, Harvard, Vancouver, ISO, and other styles
8

Hrytsyshen, Dymytrii, Iryna Suprunova та Serhii Lysak. "Класифікація економічної злочинності для цілей державного управління в контексті забезпечення державної безпеки". Central Ukrainian Scientific Bulletin. Economic Sciences, № 4(37) (2020): 9–25. http://dx.doi.org/10.32515/2663-1636.2020.4(37).9-25.

Full text
Abstract:
Classification is a special general scientific method of scientific research, which allows to establish the properties of the object of study both for the purposes of own research and for the purposes of forming new scientific knowledge. The classification model allows you to approach the object of public administration in a complex and take into account all the properties in further research. Classification as a method of study has a dual meaning for the researcher: from the outside, it is a method that contributes to the study of the system and order; from the internal, it is a technique that determines the completeness and correctness of the conclusions of the study. Classification of economic crimes from the standpoint of public administration will fully assess their properties, which determine the level of threat to national security. Economic crime is not a new phenomenon in Ukraine or in the world. Accordingly, the issue of economic crime has interested scientists for quite some time. The article investigates and systematizes the classification of economic crime in scientific and educational literature. Based on the presented approaches to the classification of economic crimes in scientific, reference and educational literature, the directions of their systematization were determined: by general components of economic activity: by violation of principles of economic activity, by sphere of economic relations. by the spheres of public relations that regulate economic activity, by the content of the committed crime, by the way of committing the crime, by the subjective features. The approaches proposed by scientists to the classification of economic crime are mostly determined by criminal law in force in a country, and therefore do not fully meet the objectives of public administration in the context of combating economic crime as a threat to national security. That is why the author's classification model of economic crime was developed for the purposes of public administration. The presented classification model of economic crime allows to approach economic crime as an object of public administration in a complex and to consider all properties at formation of innovative mechanisms of counteraction.
APA, Harvard, Vancouver, ISO, and other styles
9

Bondarenko, L. K. "Forensic art expertise in investigating art fraud." Lomonosov Law Journal 65, no. 3, 2024 (2024): 148–67. https://doi.org/10.55959/msu0130-0113-11-65-3-9.

Full text
Abstract:
Forensic means of investigating the circumstances of a case involving objects of fine art are considered. Pre-criminal and criminal situations are distinguished. Illegal actions in the sphere of circulation of objects and works of art are investigated. Attention is focused on the crime provided for in Art. 159 of the Criminal Code of the Russian Federation, which may include objects and works of art. In this regard, the following concepts are analyzed: “misleading”, “deception”, “breach of trust”, “theft”. It is proven that conducting a comprehensive forensic art examination at the initial stage is necessary to establish the subject of the crime under Article 159 of the Criminal Code of the Russian Federation. General scientific methods are used — comparison, juxtaposition; analysis, synthesis, analogy; logical methods: deduction, induction; empirical method — review of criminal legislation; forensic methods — structural-functional; building versions; private expert methods: art criticism and handwriting examination. Scientific novelty lies in: 1) clarification of the subject of the crime, according to Article 159 of the Criminal Code of the Russian Federation, related to objects of art; 2) in the classification of objects of criminal attacks in order to clarify the circumstances of the commission of crimes related to objects of art; 3) in optimizing the forensic recommendation for the appointment of a comprehensive forensic art history examination, necessary to establish the authorship, authenticity or counterfeitness of objects of art in the group of crimes related to objects of art.
APA, Harvard, Vancouver, ISO, and other styles
10

Gavrilenko, Vladimir, and Vasiliy Karpeev. "On the issue of certain types of latent crime." Current Issues of the State and Law, no. 13 (2020): 68–76. http://dx.doi.org/10.20310/2587-9340-2020-4-13-68-76.

Full text
Abstract:
We consider latent crime issues. We analyze certain types of latent crime, how to classify them, methods for analyzing types of latent crime, and policies to combat them. The relevance of the problem is determined by the need to develop a generally accepted idea of the concept and objects of both latent crime in general and its individual types. Modern programs and plans to combat crime, most commonly, do not provide for measures and methods aimed at preventing the latency of certain categories and types of crimes. Consequently, the subject of research is the criminological aspects of latent crime. We point out that a justified classification of latent crime is a classification according to which latency is divided into natural, artificial and also latency of borderline situations. We also note that the key criminological problem is not the complete eradication of latent crime, but the possibility of knowing it. In order to effectively counter latent crime, it is necessary to take measures to measure its level most accurately. In addition, we establish that the study of latent crime is not an insoluble problem, the insufficient elaboration of this problem is the result of the fact that the state is not ready to allocate the necessary amount of resources to resolve this issue.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Objects of a crime classification"

1

Kahn, Karl. "Crime and equality, or crime and punishment? : population heterogeneity and fear of crime as determinants of redistribution preferences." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:0cc102b1-c86d-4323-bfb0-3753c33baa33.

Full text
Abstract:
Despite considerable research efforts, the relationship between inequality and demand for redistribution remains a highly contested topic within comparative political economy. This paper argues that a central yet widely overlooked mechanism linking macro-level income inequality to preferences for redistribution has to with the micro-level implications of certain externalities of inequality. Focusing on fear of crime, as one such externality, I argue that because (i) in- equality and crime are positively related, and (ii) because crime and fear of crime have a negative effect in individual utility, it follows that increasing in- equality should have a positive effect on support for redistribution. Importantly, however, the argument of this paper also recognises that redistribution is but one of several means through which a concern about crime can be addressed, with the most relevant alternatives being increased policing and harsher punitive measures. Drawing on literatures in criminology and political sociology, I theorise that a key determinant of this choice | between redistribution and policing/punishment as alternative approaches to dealing with crime | is the level of ethnic heterogeneity in the population. Taken together, therefore, this paper's argument implies that inequality will have differential effects on support for redistribution in different contexts: in cases where the population is homogenous, fear of crime - and by consequence inequality - will boost demand for redistribution, whilst no such effects will follow in contexts of high heterogeneity. Using a two-step statistical methodology, I analyse Eurobarometer and ESS data from 21 OECD countries and find persuasive empirical support for my theoretical expectations. Fear of crime is more strongly associated to support for redistribution when the level of population heterogeneity remains low, whilst the opposite holds true for the relationship between fear of crime and support for policing and punishment.
APA, Harvard, Vancouver, ISO, and other styles
2

Csakany, Peter. "Classification of 3D objects from mesh surfaces." Thesis, Heriot-Watt University, 2001. http://hdl.handle.net/10399/463.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Feilzer, Martina Yvonne. "The 'crime scene' experiment : improving public knowledge through the provision of factual information on crime and criminal justice." Thesis, University of Oxford, 2007. http://ora.ox.ac.uk/objects/uuid:d8834e3d-996d-400a-8c71-8fb1f3bb6a2b.

Full text
Abstract:
This thesis explores the relationship between crime, media, and public opinion of crime and criminal justice. It sets out current levels of knowledge and contemporary debates in each of the three academic disciplines devoted to these aspects of social life, and discusses how they relate to each other. It focuses on the capacity of information and public education to influence levels of public knowledge of and, as a secondary concern, attitudes towards, crime and criminal justice. The empirical research at the heart of the thesis employed a mixed methods research study drawing on quantitative – experimental research using a public opinion survey – as well as qualitative research methods – in-depth interviews and contextual data. The experimental research, the Oxford Public Opinion Survey and the publication of the Crime Scene column, was designed to measure the impact of providing factual information about crime and criminal justice to the public in a naturalistic way, i.e. by using a local newspaper column as the conveyor of such information. The key finding from the research was that readership of the column was low and that the column had no measurable impact on readers. Overall, the research findings suggest that interest in, take-up, and retention of factual information on crime and criminal justice is not as high as previous empirical research has suggested. The Crime Scene study has implications for sociological theories of crime and punishment which rely on simplistic orthodoxies concerning the media’s importance in influencing public opinion on crime and criminal justice and the related assumption that ‘the public’ is straightforwardly punitive.
APA, Harvard, Vancouver, ISO, and other styles
4

Brandin, Martin, and Roger Hamrén. "Classification of Ground Objects Using Laser Radar Data." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1572.

Full text
Abstract:
<p>Accurate 3D models of natural environments are important for many modelling and simulation applications, for both civilian and military purposes. When building 3D models from high resolution data acquired by an airborne laser scanner it is de-sirable to separate and classify the data to be able to process it further. For example, to build a polygon model of a building the samples belonging to the building must be found.</p><p>In this thesis we have developed, implemented (in IDL and ENVI), and evaluated algorithms for classification of buildings, vegetation, power lines, posts, and roads. The data is gridded and interpolated and a ground surface is estimated before the classification. For the building classification an object based approach was used unlike most classification algorithms which are pixel based. The building classifica-tion has been tested and compared with two existing classification algorithms. </p><p>The developed algorithm classified 99.6 % of the building pixels correctly, while the two other algorithms classified 92.2 % respective 80.5 % of the pixels correctly. The algorithms developed for the other classes were tested with thefollowing result (correctly classified pixels): vegetation, 98.8 %; power lines, 98.2 %; posts, 42.3 %; roads, 96.2 %.</p>
APA, Harvard, Vancouver, ISO, and other styles
5

Kühne, Gerald. "Motion based segmentation and classification of video objects." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10605031.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Edwards, Joseph Richard 1971. "Acoustic classification of buried objects with mobile sonar platforms." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/37568.

Full text
Abstract:
Thesis (Ph. D. in Ocean Engineering)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.<br>Includes bibliographical references (p. 229-237).<br>In this thesis, the use of highly mobile sonar platforms is investigated for the purpose of acoustically classifying compact objects on or below the seabed. The extension of existing strategies, including synthetic aperture sonar and conventional imaging, are explored within the context of the buried object problem. In particular, the need to employ low frequencies for seabed penetration is shown to have a significant impact both due to the relative length of the characteristic scattering mechanisms and due to the interface effects on the target scattering. New sonar strategies are also shown that exploit incoherent wide apertures that are created by multiple sonar platforms. For example, target shape can be inverted by mapping the scattered field from the target with a team of receiver vehicles. A single sonar-adaptive sonar platform is shown to have the ability to perform hunting and classification tasks more efficiently than its pre-programmed counterpart. While the monostatic sonar platform is often dominated by the source component, the bistatic or passive receiver platform behavior is controlled by the target response. The sonar-adaptive platform trajectory, however, can result in the platform finishing its classification effort out of position to complete further tasks.<br>(cont.) Within the context of a larger mission, the use of predetermined adaptive behaviors is shown to provide improved detection and classification performance while minimizing the risk to the overall mission. Finally, it is shown that multiple sonar-adaptive platforms can be used to create new sonar strategies for hunting and classifying objects by shape and content. The ability to sample the scattered field from the target across a wide variety of positions allows an analysis of the aspect-dependent behavior of the target. The aspect-dependence of the specular returns indicate the shape of the target, while the secondary returns from an elastic target are also strongly aspect-dependent. These features are exploited for improved classification performance in the buried object hunting mission.<br>by Joseph R. Edwards.<br>Ph.D.in Ocean Engineering
APA, Harvard, Vancouver, ISO, and other styles
7

Schwanebeck, Wieland. "Beatrix Hesse. The English Crime Play in the Twentieth Century. Crime Files: Review." De Gruyter, 2017. https://tud.qucosa.de/id/qucosa%3A71155.

Full text
Abstract:
In a 2014 episode of Toast of London, a highly successful Channel 4 sitcom, protagonist Steven Toast, a dim-witted London-based actor, joins the cast of legendary stage-play The Moose Trap, which is, of course, modelled on Agatha Christie’s successful West End whodunit, The Mousetrap. When Toast accidentally spoils the play’s ending during an interview, the play soon finds itself without an audience, which leads to some of the geriatric cast members literally dying on stage.
APA, Harvard, Vancouver, ISO, and other styles
8

Jacobsen, Dawn. "Classification of Toolmark Surfaces on Zipper Teeth." Thesis, University of North Texas, 1999. https://digital.library.unt.edu/ark:/67531/metadc2248/.

Full text
Abstract:
This study proposes the classification of the toolmark under the heads of zipper teeth as a subclass characteristic as outlined by the Association of Firearm and Toolmark Examiners (AFTE). Two separate cases in which zipper teeth were found at crime scenes prompted this study. Brass zipper teeth manufactured by YKK were taken from 20 pairs of jeans and studied using a Reichert comparison microscope at 4X power. Photographs were taken and over 750 comparisons made. It was found that the toolmarks on each side on the 20 zippers were unique and independent of all other sides. The observations made in this study indicate that classifying zipper teeth toolmarks as a subclass characteristic is valid.
APA, Harvard, Vancouver, ISO, and other styles
9

Cichocki, Radoslaw. "Classification of objects in images based on various object representations." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5774.

Full text
Abstract:
Object recognition is a hugely researched domain that employs methods derived from mathematics, physics and biology. This thesis combines the approaches for object classification that base on two features – color and shape. Color is represented by color histograms and shape by skeletal graphs. Four hybrids are proposed which combine those approaches in different manners and the hybrids are then tested to find out which of them gives best results.<br>Mail the author at radoslaw.cichocki(at)gmail.com
APA, Harvard, Vancouver, ISO, and other styles
10

LIU, HUI. "Classification and prediction for flying objects based on behavior model." Thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-22207.

Full text
Abstract:
This master thesis relates to machine vision system and object classification. The aim of this paper is to classify the flying objects in images in a computer vision system, for example, an eagle, kite or airplane. In this thesis, large amounts of data will be analyzed and a behavior model will be built for each object as important steps towards improving and automating the object classification system. The application of this thesis is to reduce the deaths of golden and bald eagles due to wind blades. In this thesis work, a new effective method is presented, namely, a stereo vision system, which is applied in feature selection based on this object classification. Several features are primarily extracted, including the flying height, speed, size and degree of changes in the object parameters.  For image processing and feature extraction, the video acquisition is the first and essential step. Due to the limitation both of equipment and location, the captured videos still do not allow for the collection of sufficient data. For the classification of two objects, a Support Vector Machine (SVM) and Library for Support Vector Machine (LIBSVM) have been employed and implemented in MATLAB. In addition, a preliminary study in relation to the idea of multi-class classification has been conceived and tested by means of an experiment.  In relation to building a behavior model, the various feature properties and characteristics were beneficial with regards to developing the accuracy and robustness of the final classification and recognition results. The results gathered from these two methods in terms of SVM and LIBSVM are compared and analyzed in order to identify their differences and to determine a better solution. Additionally, the possible future work for this project will be discussed. Results show that 98% of the flying objects can be currently classified by using OVO SVMs and the OVR SVMs. Based on the results of the classification, 85.82% of the flying objects could be predicted correctly. Key words: machine vision system, object classification, behavior model, stereo vision system, image processing, feature extraction, SVM, LIBSVM, MATLAB
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Objects of a crime classification"

1

Douglas, John E. Crime classification manual. Lexington Books, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

E, Douglas John, ed. Crime classification manual. Simon & Schuster, 1993.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

E, Douglas John, ed. Crime classification manual. Jossey-Bass Publishers, 1997.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

E, Douglas John, ed. Crime classification manual. Lexington Books, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Rieger, J. H. On the classification of news of piecewise smooth objects. Queen Mary College, Department of Computer Science and Statistics, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

E, Douglas John, Burgess Ann Wolbert, and Burgess Allen G, eds. Pocket guide to the Crime classification manual. Lexington Books, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Law Reform Commission of Canada. Classification of offences. Law Reform Commission of Canada, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Shubert, Steven Blake. Classification in the CHIN humanities databases. Canadian Heritage Information Network, 1995.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Kryvochenko, L. M. Klasyfikat︠s︡ii︠a︡ zlochyniv za stupenem ti︠a︡z︠h︡kosti v Kryminalʹnomu kodeksi Ukraïny: Monohrafii︠a︡. I︠U︡rinkom Inter, 2010.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Chubarev, V. L. Ti͡a︡zhestʹ prestupnogo dei͡a︡nii͡a︡. "Vyshta shkola", 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Objects of a crime classification"

1

Huchard, Marianne, Robert Godin, and Amedeo Napoli. "Objects and Classification." In Object-Oriented Technology. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44555-2_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Convertini, Vito Nicola, and Gianni Bruno. "Classification of Learning Objects." In Encyclopedia of the Sciences of Learning. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_71.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Bezhaev, Anatoly Yu, and Vladimir A. Vasilenko. "Classification of Spline Objects." In Variational Theory of Splines. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3428-7_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Wei, William. "Fingerprinting Objects for the Control of Illegal Trafficking." In Art Crime. Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1007/978-1-137-40757-3_6.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Kamakura, Mawo, Takeshi Oishi, Jun Takamatsu, and Katsushi Ikeuchi. "Classification of Bayon Faces." In Digitally Archiving Cultural Objects. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-75807_19.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Gerstenblith, Patty. "Returning Illegally Trafficked Cultural Objects." In Cultural Property Crime and the Law. Routledge, 2024. http://dx.doi.org/10.4324/9781003363804-8.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Kiel, R., and M. Schader. "Consistent Completion of Incomplete Data Objects." In Classification and Knowledge Organization. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-59051-1_30.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Baptista, Marcia, Luis Fernandes, and Paulo Chaves. "Tracking and Classification of Aerial Objects." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38822-5_18.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Li, Zhanchuang, Jianmin Jiang, and Guoqiang Xiao. "SVM-Based Classification of Moving Objects." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10512-8_5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Ivezić, Željko, and Moshe Elitzur. "Infrared Classification of Young Stellar Objects." In The Role of Dust in the Formation of Stars. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-540-68594-4_73.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Objects of a crime classification"

1

G, Balaji, and Kokila G. "Crime Hotspot Classification Using Machine Learning." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10968834.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Joseph, Ajay Mathew, Fath U. Min Ullah, and Estefania Talavera. "Body-part Tubelet Transformer for Human-Related Crime Classification." In 2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). IEEE, 2024. http://dx.doi.org/10.1109/avss61716.2024.10672609.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Rangata, Mapitsi Roseline, and Tshephisho Joseph Sefara. "Classification of Crime-related News Titles using Machine Learning Methods." In 2024 International Conference on Electrical, Communication and Computer Engineering (ICECCE). IEEE, 2024. https://doi.org/10.1109/icecce63537.2024.10823540.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Ponnusamy, R., Veeramalai Sankaradass, HarshivKrishna M, Sre Sandhya K, Bharath Sampath, and Aashika B. "Utilizing Machine Learning Techniques for Crime Classification Under the Indian Penal Code (IPC) Based on Crime Reporting Data." In 2025 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI). IEEE, 2025. https://doi.org/10.1109/icdsaai65575.2025.11011787.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

García, Andrés, Brandon Martínez, Zaid Moroyoqui, Kenia Picos, and Ulises Orozco-Rosas. "LiDAR-based classification of objects and terrain." In Optics and Photonics for Information Processing XVIII, edited by Khan M. Iftekharuddin, Abdul A. S. Awwal, Andrés Márquez, and Victor Hugo Diaz-Ramirez. SPIE, 2024. http://dx.doi.org/10.1117/12.3028632.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kumar, M. Manoj, U. Kumaran, D. Shravani, Bommaka Uday Kumar, Makkineni Rajesh, and K. Sireesha. "Deep Learning for Classification of Salient Object Classification in Unmanned Crime Spot." In 2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT). IEEE, 2023. http://dx.doi.org/10.1109/iceeict56924.2023.10157964.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Fernandez Arguedas, V., and E. Izquierdo. "Object classification based on behaviour patterns." In 4th International Conference on Imaging for Crime Detection and Prevention 2011 (ICDP 2011). IET, 2011. http://dx.doi.org/10.1049/ic.2011.0112.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

A. Gaus, Yona Falinie, Neelanjan Bhowmik, Brian K. Isaac-Medina, and Toby P. Breckon. "Visible to infrared transfer learning as a paradigm for accessible real-time object detection and classification in infrared imagery." In Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies IV, edited by Henri Bouma, Robert J. Stokes, Yitzhak Yitzhaky, and Radhakrishna Prabhu. SPIE, 2020. http://dx.doi.org/10.1117/12.2573968.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Abu Hana, Ricardo O., Cinthia O. A. Freitas, Luiz S. Oliveira, and Flávio Bortolozzi. "Crime scene classification." In the 2008 ACM symposium. ACM Press, 2008. http://dx.doi.org/10.1145/1363686.1363789.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Wang, Pengfei, Yu Fan, Shuzi Niu, Ze Yang, Yongfeng Zhang, and Jiafeng Guo. "Hierarchical Matching Network for Crime Classification." In SIGIR '19: The 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2019. http://dx.doi.org/10.1145/3331184.3331223.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Objects of a crime classification"

1

Morrison, Frank, Torquil Smith, Alex Becker, and Erika Gasperikova. Detection and Classification of Buried Metallic Objects UX-1225. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/840326.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Cheok, Geraldine S., Marek Franaszek, Afzal Godil, Kamel S. Saidi, Roger Eastman, and Tsai Hong. Towards a Classification System of Manufacturing Objects for the Evaluation of Perception Systems. National Institute of Standards and Technology, 2014. http://dx.doi.org/10.6028/nist.ir.7985.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Schock, Steven G., and Lester R. LeBlanc. Sonar Detection and Classification of Buried or Partially Buried Objects in Cluttered Environments. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada628279.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Schock, Steven G. Sonar Detection and Classification of Buried or Partially Buried Objects in Cluttered Environments Using UUVs. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada627089.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Bragdon, Sophia, Vuong Truong, and Jay Clausen. Environmentally informed buried object recognition. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45902.

Full text
Abstract:
The ability to detect and classify buried objects using thermal infrared imaging is affected by the environmental conditions at the time of imaging, which leads to an inconsistent probability of detection. For example, periods of dense overcast or recent precipitation events result in the suppression of the soil temperature difference between the buried object and soil, thus preventing detection. This work introduces an environmentally informed framework to reduce the false alarm rate in the classification of regions of interest (ROIs) in thermal IR images containing buried objects. Using a dataset that consists of thermal images containing buried objects paired with the corresponding environmental and meteorological conditions, we employ a machine learning approach to determine which environmental conditions are the most impactful on the visibility of the buried objects. We find the key environmental conditions include incoming shortwave solar radiation, soil volumetric water content, and average air temperature. For each image, ROIs are computed using a computer vision approach and these ROIs are coupled with the most important environmental conditions to form the input for the classification algorithm. The environmentally informed classification algorithm produces a decision on whether the ROI contains a buried object by simultaneously learning on the ROIs with a classification neural network and on the environmental data using a tabular neural network. On a given set of ROIs, we have shown that the environmentally informed classification approach improves the detection of buried objects within the ROIs.
APA, Harvard, Vancouver, ISO, and other styles
6

Majd, Farjam. Two new parallel processors for real time classification of 3-D moving objects and quad tree generation. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.5301.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Bishop, Megan, Vuong Truong, Sophia Bragdon, and Jay Clausen. Comparing the thermal infrared signatures of shallow buried objects and disturbed soil. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/49415.

Full text
Abstract:
The alteration of physical and thermal properties of native soil during object burial produces a signature that can be detected using thermal infrared (IR) imagery. This study explores the thermal signature of disturbed soil compared to buried objects of different compositions (e.g., metal and plastic) buried 5 cm below ground surface (bgs) to better understand the mechanisms by which soil disturbance can impact the performance of aided target detection and recognition (AiTD/R). IR imagery recorded every five minutes were coupled with meteorological data recorded on 15-minute intervals from 1 July to 31 October 2022 to compare the diurnal and long-term fluctuations in raw radiance within a 25 × 25 pixel area of interest (AOI) above each target. This study examined the diurnal pattern of the thermal signature under several varying environmental conditions. Results showed that surface effects from soil disturbance increased the raw radiance of the AOI, strengthening the contrast between the object and background soil for several weeks after object burial. Enhancement of the thermal signature may lead to expanded windows of object visibility. Target age was identified as an important element in the development of training data sets for machine learning (ML) classification algorithms.
APA, Harvard, Vancouver, ISO, and other styles
8

Ross, Andrew, David Johnson, Hai Le, Danny Griffin, Carl Mudd, and David Dawson. USACE Advanced Modeling Object Standard : Release 1.0. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42152.

Full text
Abstract:
The U.S. Army Corps of Engineers (USACE) Advanced Modeling Object Standard (AMOS) has been developed by the CAD/BIM Technology Center for Facilities, Infrastructure, and Environment to establish standards for support of the Advanced Modeling process within the Department of Defense (DoD) and the Federal Government. The critical component of Advanced Modeling is the objects themselves- and either make the modeling process more difficult or more successful. This manual is part of an initiative to develop a nonproprietary Advanced Modeling standard that incorporates both vertical construction and horizontal construction objects that will address the entire life cycle of facilities within the DoD. The material addressed in this USACE Advanced Modeling Object Standard includes a classification organization that is needed to identify models for specific use cases. Compliance with this standard will allow users to know whether the object model they are getting is graphically well developed but data poor or if it does have the data needed for creating contract documents. This capability will greatly reduce the designers’ efforts to either build an object or search/find/edit an object necessary for the development of their project. Considering that an advanced model may contain hundreds of objects this would represent a huge time savings and improve the modeling process.
APA, Harvard, Vancouver, ISO, and other styles
9

Mazari, Mehran, Yahaira Nava-Gonzalez, Ly Jacky Nhiayi, and Mohamad Saleh. Smart Highway Construction Site Monitoring Using Artificial Intelligence. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2336.

Full text
Abstract:
Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. Due to the lack of a comprehensive image database specifically developed for transportation infrastructure construction projects, the first portion of this study focused on preparing a comprehensive database of annotated images for various classes of equipment and machinery that are commonly used in roadway construction and rehabilitation projects. The second part of the project focused on training the deep learning models and improving the accuracy of the classification and detection algorithms. The outcomes of the trained and improved deep learning classification model were promising in terms of the precision and accuracy of the model in detecting specific objects at a highway construction site. It should be noted that the scope of this project was limited to the image and video data recorded from the ground-level and cannot be extended to Uncrewed Aerial System (UAS) data. This study provides valuable insights on the potentials of AI and deep learning to improve the monitoring and thus safety and efficiency of transportation infrastructure construction.
APA, Harvard, Vancouver, ISO, and other styles
10

Wilson, D., Steven Peckham, Max Krackow, Sora Haley, Sophia Bragdon, and Jay Clausen. Discriminating buried munitions based on physical models for their thermal response. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49749.

Full text
Abstract:
Munitions and other objects buried near the Earth’s surface can often be recognized in infrared imagery because their thermal and radiative properties differ from the surrounding undisturbed soil. However, the evolution of the thermal signature over time is subject to many complex interacting processes, including incident solar radiation, heat conduction in the ground, longwave radiation from the surface, and sensible and latent heat exchanges with the atmosphere. This complexity makes development of robust classification algorithms particularly challenging. Machine-learning algorithms, although increasingly popular, often require large training datasets including all environments to which they will be applied. Algorithms incorporating an understanding of the physical processes underlying the thermal signature potentially provide improved performance and mitigate the need for large training datasets. To that end, this report formulates a simplified model for the energy exchange near the ground and describes how it can be incorporated into maximum-likelihood ratio and Bayesian classifiers capable of distinguishing buried objects from their surroundings. In particular, a version of the Bayesian classifier is formulated that leverages the differing amplitude and phase response of a buried object over a 24-hour period. These algorithms will be tested on experimental data in a future study.
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Objects of a crime classification' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography