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Journal articles on the topic 'Crime detection'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Wong, Gabriel, Matthew Manning, T. Wing Lo, and Shane D. Johnson. "Triad influence on the detection of crime in Hong Kong." PLOS ONE 19, no. 2 (2024): e0297145. http://dx.doi.org/10.1371/journal.pone.0297145.

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We use bootstrap data envelopment analysis, adjusting for endogeneity, to examine police efficiency in detecting crime in Hong Kong. We address the following: (i) is there a correlation between the detection of crime and triad influence? (ii) does the level of triad influence affect the efficiency in translating inputs (police strength) into outputs (crime detection)? and (iii) how can the allocation of policing resources be adjusted to improve crime detection? We find that nighty-eight percent of Hong Kong police districts in our sample were found to be inefficient in the detection of crime.

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2

Preethi, B. Meena, C. Sunitha, M. Parameshvar, B. Dharshini, and S. Gokul. "Emotion Detection using HOG for Crime Detection." Indian Journal Of Science And Technology 16, no. 41 (2023): 3617–26. http://dx.doi.org/10.17485/ijst/v16i41.1580.

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3

Mohamad Zamri, Nurul Farhana, Nooritawati Md Tahir, Megat Syahirul Amin Megat Ali1, Nur Dalila Khirul Ashar, and Ali Abd Al-misreb. "Mini-review of Street Crime Prediction and Classification Methods." Jurnal Kejuruteraan 33, no. 3 (2021): 391–401. http://dx.doi.org/10.17576/jkukm-2021-33(3)-02.

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Crime rates are one of the biggest problems in today’s modern society, especially in urban cities. Various techniques on crime prediction and detection have been developed by previous researchers in reducing the crime rates that keep increasing throughout the year as well as to assist the government authorities in combating crimes. These include studies on forecasting crime activities based on both primary and secondary data that include numerical data, statistics, video, and images related to various categories of crimes. Thus, in this study, a mini-review is conducted related to the database

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4

Potapov, Sergey A. "The significance of the criminal-law and criminalistic concepts of crime in the detection and investigation." Current Issues of the State and Law, no. 18 (2021): 309–19. http://dx.doi.org/10.20310/2587-9340-2021-5-18-309-319.

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The relevance of work is due to a comprehensive study of the meaning of the criminal-law and criminalistic concepts of crime in the detection and investigation. The purpose of work is to analyze the criminal-law and criminalistic concepts of crime as systems, as well as to consider their main elements. The implementation of this purpose is achieved by using the laws of dialectics, formal logic and using of general scientific and private scientific research methods. We examine such criminal-law and criminalistic categories as crime, elements and body of crime, criminal activity, and mechanism o

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Pertsev, R. "RESEARCH ON MODERN FORENSIC METHODS OF DETECTION, RECORD, SEIZURE OF SHOEPRINTS AND THEIR FURTHER ACCOUNTING FOR CRIME DETECTION." Theory and Practice of Forensic Science and Criminalistics 21, no. 1 (2020): 106–19. http://dx.doi.org/10.32353/khrife.1.2020_07.

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Shoe prints that have been traced by crime scene investigators at the crime scene can provide information relating to a criminal or a group of criminals that have committed it, and serve as evidence while pre-trial investigation. Furthermore, shoe prints provide information on the possible participation of the same person in different types of crimes (to integrate crimes). At present, the number of crimes related to stealing civilian properties, including robbery, has significantly increased as a result of economic crisis in many countries around the world. As the studies and the p

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Slinko, Sergey V., Pylyp S. Yepryntsev, Artem O. Shapar, Dmytro B. Sanakoiev, and Alina H. Harkusha. "Modern indicators of financial crimes detection and their prevention in Ukraine." Revista Amazonia Investiga 10, no. 44 (2021): 61–72. http://dx.doi.org/10.34069/ai/2021.44.08.6.

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The increase in the level of financial crime is caused by the technological development, weak moni-toring of financial institutions, low level of international cooperation in terms of combating these types of crimes. The paper aims to develop effective ways to combat financial crimes in Ukraine. With the help of a systematic analysis of financial crime modern indicators, theoretical sources, prac-tical measures and international experience, the main indicators of financial crimes are identified. Such indicators are the use of false documents and other people's accounts, international payment s

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Slinko, Sergey V., Pylyp S. Yepryntsev, Artem O. Shapar, Dmytro B. Sanakoiev, and Alina H. Harkusha. "Modern indicators of financial crimes detection and their prevention in Ukraine." Revista Amazonia Investiga 10, no. 44 (2021): 61–72. http://dx.doi.org/10.34069/ai/2021.44.08.6.

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The increase in the level of financial crime is caused by the technological development, weak moni-toring of financial institutions, low level of international cooperation in terms of combating these types of crimes. The paper aims to develop effective ways to combat financial crimes in Ukraine. With the help of a systematic analysis of financial crime modern indicators, theoretical sources, prac-tical measures and international experience, the main indicators of financial crimes are identified. Such indicators are the use of false documents and other people's accounts, international payment s

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8

Dr., S. S. Sreeja Mole, K. Sujatha Dr., Devi Kala Rathinam D., Santhiya Grace A., and K. Bhuvana M. "THE CRIME DETECTION SYSTEM FOR WOMEN." International Journal of Computational Research and Development 3, no. 1 (2018): 39–43. https://doi.org/10.5281/zenodo.1165250.

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India is most traditional country throughout the world. In India they give more respect for the women. Nowadays there are many crimes occur in our major cities like Delhi, Mumbai etc. In India, for every one hour 26 crimes occurs against women and recent survey says that for every two minutes the occurrence of crime is one. In last decades the women’s are uneducated and they completely depend on men’s. But now days the women’s are educated and there are travelling throughout the world. Our government proposed the act Dowry Prohibition Act, 1961. Using this act the dowry has b

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9

Mazurenko, Pavel Nikolaevich, Ramil Rashitovich Rahmatullin, and Nail Failevich Fayzrakhmanov. "Crime detection – russian and foreign experience." Laplage em Revista 6, Extra-C (2020): 271–75. http://dx.doi.org/10.24115/s2446-622020206extra-c651p.271-275.

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The article discusses the issues of crime detection as one of the criteria for the effectiveness of the law enforcement agencies. Every year the number of undetected crimes remains at a consistently high level. This confirms the relevance of the problem under consideration and indicates the need for further developments in this direction. The authors managed to conclude that the full definition of the term “crime detection” is not presented in any legislative act, i.e. this scientific category has actually always been outside the legal field, which led to its arbitrary interpretation by indivi

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10

Junoh, Ahmad Kadri, Muhammad Naufal Mansor, Alezar Mat Ya'acob, Farah Adibah Adnan, Syafawati Ab Saad, and Nornadia Mohd Yazid. "Crime Detection with ICA and Artificial Intelligent Approach." Advanced Materials Research 816-817 (September 2013): 616–22. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.616.

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The Rise of Crime in Malaysia reported that violent crimes comprised only 10% of reported crimes each year and the majority of crimes, 90%, were classified as property crimes. However, the ratio of police to population is 3.6 officers to 1,000 citizens in Malaysia. This lack of manpower sources ratios alone are not a comprehensive afford of crime fighting capabilities. Thus, we proposed an Artificial Intelligent Techniques to determine the behaviour of the burglar with Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and k Nearest Neighbor (k-NN) Classifier. This system

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11

K, Vijay, and Amal Prakash. "A Systematic Review on Tanpin Kandri Based Crime Prediction." Remittances Review 7, no. 2 (2022): 01–11. http://dx.doi.org/10.47059/rr.v7i2.2407.

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Predictive policing refers to the potential preventive measure to fight crimes in the modern age. Crimes are social issues that have a negative effect on society. The number of cases filed under the Indian Penal Code (IPC) in 2020 increased by over 430 percent compared to the same year-ago period. Data analytics is the process of inspecting, transforming, and modelling unstructured data into useful information. Predictive policing and crime analytics with Artificial intelligence increase attention among a multifarious scientific community. Crime pattern analysis is the computational approach t

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12

Prof., Suman Acharya. "Crime Analytics using Machine Learning." International Journal of Inventive Engineering and Sciences (IJIES) 10, no. 3 (2023): 1–5. https://doi.org/10.35940/ijies.F7444.0310323.

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<strong>Abstract: </strong>Crime is one of the most significant and pervasive problems in our society, and preventing it is a crucial duty. A large number of crimes are perpetrated each day. Maintaining and analyzing crime data to forecast and solve crimes is the current issue. This project analyzes a large dataset of crimes and predicts future crimes based on conditions. This project uses data science and machine learning for India's crime data prediction. Thus, Decision Tree, Logistic Regression, Multi-Regression, k-NN, Lasso & Ridge, and Random Forest are all involved in the supervi

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13

Bond, John W. "Maximising the Opportunities to Detect Domestic Burglary with DNA and Fingerprints." International Journal of Police Science & Management 9, no. 3 (2007): 287–98. http://dx.doi.org/10.1350/ijps.2007.9.3.287.

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The impact on the detection and reduction of domestic burglary by a prioritisation of forensic resources and processing over a six-month study period is examined. Targets were set and monitored for the twin factors of increased attendance at crime scenes and increased timeliness of processing both DNA and fingerprint samples. The results showed that it is possible to increase the number of primary detections derived from DNA and fingerprints with the DNA increase being statistically significant. This increase was accompanied by a decrease in reported domestic burglaries. After its completion,

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14

Gao, Jerry, Jingwen Shi, Priyanka Balla, et al. "Camera-Based Crime Behavior Detection and Classification." Smart Cities 7, no. 3 (2024): 1169–98. http://dx.doi.org/10.3390/smartcities7030050.

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Increasing numbers of public and private locations now have surveillance cameras installed to make those areas more secure. Even though many organizations still hire someone to monitor the cameras, the person hired is more likely to miss some unexpected events in the video feeds because of human error. Several researchers have worked on surveillance data and have presented a number of approaches for automatically detecting aberrant events. To keep track of all the video data that accumulate, a supervisor is often required. To analyze the video data automatically, we recommend using neural netw

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15

Apene, Oghenevovwero Zion, Nachamada Vachaku Blamah, and Gilbert Imuetinyan Osaze Aimufua. "Advancements in Crime Prevention and Detection: From Traditional Approaches to Artificial Intelligence Solutions." European Journal of Applied Science, Engineering and Technology 2, no. 2 (2024): 285–97. https://doi.org/10.59324/ejaset.2024.2(2).20.

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Crime prevention and detection are critical components of public safety in any nation. Traditionally, crime prevention and detection approaches relied on human intuition and limited data, resulting in reactive and resource-intensive methods. However, recent advancements in artificial intelligence (AI) offer a paradigm shift, enabling proactive, data-driven approaches. This study explores the evolution from conventional crime prevention and detection methods to cutting-edge AI solutions. It employs a literature survey, local observation, and global news approach to examine the current state of

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16

Rony, Md Sumon, Sagor Chandra Bakchy, and Hadisur Rahman. "Crime Detection using Data Mining Techniques." Computer Science & Engineering: An International Journal 10, no. 5 (2020): 1–5. http://dx.doi.org/10.5121/cseij.2020.10501.

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As crime rates keep spiraling each day, new challenges are faced by law enforcement agencies. They have to keep their on the lookout for any signs criminal activity. The law enforcement agencies should therefore be able to predict such increase or decrees or trends in crime. Such as theft, Killing. Crime that may occur in a particular area in a particular month, year, any timespan. Data mining is defined as a process of discovering hidden valuable knowledge by analyzing large amounts of data, which is stored in databases or data warehouse, using various data mining techniques such as machine l

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17

Lubin, A. F. "On the Concept of “Disclosure of Crimesˮ". Juridical science and practice 18, № 3 (2023): 43–50. http://dx.doi.org/10.25205/2542-0410-2022-18-3-43-50.

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The article discusses various approaches to the definition of the concept of “crime detectionˮ. Based on the coincidence of the purpose of the forensic methodology for investigating crimes and the purpose of the criminal process, a new interpretation of the concept under study is proposed. The disclosure of a crime must be proved by the results of the activities of the bodies of inquiry and preliminary investigation. These results should be presented by a system of accusatory evidence for the prosecutor to make a legal, fair and justified procedural decision to transfer the criminal case to co

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18

Apene, Oghenevovwero Zion, Nachamada Vachaku Blamah, and Gilbert Imuetinyan Osaze Aimufua. "Advancements in Crime Prevention and Detection: From Traditional Approaches to Artificial Intelligence Solutions." European Journal of Applied Science, Engineering and Technology 2, no. 2 (2024): 285–97. http://dx.doi.org/10.59324/ejaset.2024.2(2).20.

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Crime prevention and detection are critical components of public safety in any nation. Traditionally, crime prevention and detection approaches relied on human intuition and limited data, resulting in reactive and resource-intensive methods. However, recent advancements in artificial intelligence (AI) offer a paradigm shift, enabling proactive, data-driven approaches. This study explores the evolution from conventional crime prevention and detection methods to cutting-edge AI solutions. It employs a literature survey, local observation, and global news approach to examine the current state of

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19

Acharya, Prof Suman. "Crime Analytics using Machine Learning." International Journal of Inventive Engineering and Sciences 10, no. 3 (2023): 1–5. http://dx.doi.org/10.35940/ijies.f7444.0310323.

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Crime is one of the most significant and pervasive problems in our society, and preventing it is a crucial duty. A large number of crimes are perpetrated each day. Maintaining and analyzing crime data to forecast and solve crimes is the current issue. This project analyzes a large dataset of crimes and predicts future crimes based on conditions. This project uses data science and machine learning for India's crime data prediction. Thus, Decision Tree, Logistic Regression, Multi-Regression, k-NN, Lasso & Ridge, and Random Forest are all involved in the supervised classification problem. Pre

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20

G ANIL KUMAR, G. ANIL KUMAR, D. VENKATESH D VENKATESH, and KANTE RAMESH. "Credit Crime Detection By Using Multilayer System." International Journal of Scientific Research 2, no. 7 (2012): 177–80. http://dx.doi.org/10.15373/22778179/july2013/59.

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21

Baidari, Dr Ishwar, and S. P. Sajjan. "Location Based Crime Detection Using Data Mining." Bonfring International Journal of Software Engineering and Soft Computing 6, Special Issue (2016): 208–12. http://dx.doi.org/10.9756/bijsesc.8279.

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22

Tamilarasi, T., and Sangeetha Varadhan. "Crime Analysis Mapping with Intrusion Detection System." International Journal of Research Publication and Reviews 5, no. 5 (2024): 6411–16. http://dx.doi.org/10.55248/gengpi.5.0524.1106.

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23

Khyioon Abdalrdha, Zainab, Abbas Mohsin Al-Bakry, and Alaa K. Farhan. "A Survey on Cybercrime Using Social Media." Iraqi Journal for Computers and Informatics 49, no. 1 (2023): 52–65. http://dx.doi.org/10.25195/ijci.v49i1.404.

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There is growing interest in automating crime detection and prevention for large populations as a result of the increased usage of social media for victimization and criminal activities. This area is frequently researched due to its potential for enabling criminals to reach a large audience. While several studies have investigated specific crimes on social media, a comprehensive review paper that examines all types of social media crimes, their similarities, and detection methods is still lacking. The identification of similarities among crimes and detection methods can facilitate knowledge an

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24

Walia, Mrs Sukhvinder Kaur, Dr Shraddha Masih, and Dr Ugrasen Suman. "An Experimental Approach for Evaluating the Performance of Clustering Techniques for Crime Detection." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–5. https://doi.org/10.55041/ijsrem40082.

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In the 21st century, when technology connects the entire world, our society suffers from modern age crime and criminals. A big challenge with the law enforcement agencies is to find and detect crimes. In machine learning, clustering algorithm is used to analyze crime related textual data focusing on identifying crime patterns from crime text data. In this research three clustering methods such as K-means, Agglomerative and DBSCAN are applied to crime reports to group similar description into clusters. These clusters were then analyzed to reveal the underlying patterns such as common crime type

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Babu, R. Buli, G. Snehal, and Aditya Satya Kiran. "Detection of Crimes Using Unsupervised Learning Techniques." APTIKOM Journal on Computer Science and Information Technologies 2, no. 1 (2020): 8–11. http://dx.doi.org/10.34306/csit.v2i1.62.

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Data mining can be used to detect model crime problems. This paper is about the importance of datamining about its techniques and how we can easily solve the crime. Crime data will be stored in criminal’s database.To analyze the data easily we have data mining technique that is clustering. Clustering is a method to group identicalcharacteristics in which the similarity is maximized or minimized. In clustering techniques also we have different typeof algorithm, but in this paper we are using the k-means algorithm and expectation-maximization algorithm. We areusing these techniques because these

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Phua, Clifton, Kate Smith-Miles, Vincent Lee, and Ross Gayler. "Resilient Identity Crime Detection." IEEE Transactions on Knowledge and Data Engineering 24, no. 3 (2012): 533–46. http://dx.doi.org/10.1109/tkde.2010.262.

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27

Phua, Clifton, Kate Smith-Miles, Vincent Lee, and Ross Gayler. "Resilient Identity Crime Detection." IEEE Transactions on Knowledge and Data Engineering 24, no. 3 (2011): 533–46. https://doi.org/10.1109/TKDE.2010.262.

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© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Deposited by shareyourpaper.org and openaccessbutton.org. We've taken reasonable steps to ensure this content doesn't violate copyright. However, if you think it does you can request a takedown by emailing help@opena

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28

Martínez-Mascorro, Guillermo A., José R. Abreu-Pederzini, José C. Ortiz-Bayliss, Angel Garcia-Collantes, and Hugo Terashima-Marín. "Criminal Intention Detection at Early Stages of Shoplifting Cases by Using 3D Convolutional Neural Networks." Computation 9, no. 2 (2021): 24. http://dx.doi.org/10.3390/computation9020024.

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Crime generates significant losses, both human and economic. Every year, billions of dollars are lost due to attacks, crimes, and scams. Surveillance video camera networks generate vast amounts of data, and the surveillance staff cannot process all the information in real-time. Human sight has critical limitations. Among those limitations, visual focus is one of the most critical when dealing with surveillance. For example, in a surveillance room, a crime can occur in a different screen segment or on a distinct monitor, and the surveillance staff may overlook it. Our proposal focuses on shopli

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29

Babu, R. Buli, G. Snehal, and P. Aditya Satya Kiran. "Detection of Crimes Using Unsupervised Learning Techniques." APTIKOM Journal on Computer Science and Information Technologies 2, no. 1 (2017): 8–11. http://dx.doi.org/10.11591/aptikom.j.csit.92.

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Data mining can be used to detect model crime problems. This paper is about the importance of data mining about its techniques and how we can easily solve the crime. Crime data will be stored in criminal’s database. To analyze the data easily we have data mining technique that is clustering. Clustering is a method to group identical characteristics in which the similarity is maximized or minimized. In clustering techniques also we have different type of algorithm, but in this paper we are using the k-means algorithm and expectation-maximization algorithm. We are using these techniques because

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30

Kiran P, Mounika B, Naveen P, Tejaswini N, and Karthik B. "Crime data anlysis using machine learning." South Asian Journal of Engineering and Technology 12, no. 3 (2022): 61–68. http://dx.doi.org/10.26524/sajet.2022.12.39.

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   Crime is one of the biggest and dominating problems in our society and its prevention is an important task. Daily there are huge numbers of crimes committed frequently. This requires keeping track of all the crimes and maintaining a database for same which may be used for future reference. The current problem faced are maintaining of proper dataset of crime and analyzing this data to help in predicting and solving crimes in future. The objective of this project is to analyze dataset which consist of numerous crimes and predicting the type of crime which may happen in futur

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Tan, Yue Sheng, Zhan Sheng Qi, and Jing Yu Wang. "Applications of Association Rules in Computer Crime Forensics." Applied Mechanics and Materials 157-158 (February 2012): 1281–86. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.1281.

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Association rules can mine the relevant evidence of computer crime from the mass of data and association rules among data items, and further mine crime laws, trends and connections among different crimes. It provides police’s case detection and crime prevention with clues and criterions. This paper firstly analyzes the application of FP-Growth algorithms in computer crime forensics, points out the defect of FP-Growth algorithms that can’t timely find the latest crime and the serious crime, and then puts some improvements of the FP-Growth algorithms and tests it by carrying out experiments. Fin

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32

Brody, Richard G., and Frank S. Perri. "Fraud detection suicide: the dark side of white-collar crime." Journal of Financial Crime 23, no. 4 (2016): 786–97. http://dx.doi.org/10.1108/jfc-09-2015-0043.

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Purpose The purpose of this paper is to explore the issue of suicide, a violent act against one’s self, as it relates to white- and red-collar crimes. White-collar crime can be described as nonviolent crime committed for financial gain. Red-collar crime describes a situation where a white-collar criminal commits an act of violence, often murder, to silence someone who is in a position to report a fraud they have perpetrated. Previous research has not addressed the issue of suicide, as it relates to white- and red-collar crime. Design/methodology/approach The analysis is conceptual, focusing on

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Gupta, Anuj Kumar, Varun Kumar Reddy Buddula, Achuthananda Reddy Polu, and Bhumeka Narra. "An Analysis of Crime Prediction and Classification Using Data Mining Techniques." International Journal of Advanced Research in Engineering and Applied Sciences 10, no. 05 (2025): 43–56. https://doi.org/10.63665/ijareas.v10i05.01.

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Crime is a serious and widespread problem in their society, thus preventing it is essential. Assignment. A significant number of crimes are committed every day. One tool for dealing with model crime is data mining. Crimes are costly to society in many ways, and they are also a major source of frustration for its members. A major area of machine learning research is crime detection. This paper analyzes crime prediction and classification using data mining techniques on a crime dataset spanning 2006 to 2016. This approach begins with cleaning and extracting features from raw data for data prepar

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OKSANA VIVCHAR. "ORGANIZATIONAL AND LEGAL MECHANISM OF FINANCIAL INVESTIGATIONS IN LAW ENFORCEMENT ACTIVITY: INFORMATION AND ANALYTICAL APPROACH." Herald of Khmelnytskyi National University 294, no. 3 (2021): 82–86. http://dx.doi.org/10.31891/2307-5740-2021-294-3-13.

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In modern conditions of turbulence of economic processes of activity of law enforcement agencies testifies that effective counteraction to crime is impossible without active use of economic knowledge. Please note that the practical effectiveness of the mechanism for detecting and investigating economic crimes depends to some extent on the study of financial information that characterizes criminal activity. Meanwhile, it should be noted that at the stage of crime detection, financial monitoring of dubious financial transactions is used, inspections and audits of financial and economic activitie

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Mahida, Ankur. "Cross - Border Financial Crime Detection - A Review Paper." International Journal of Science and Research (IJSR) 9, no. 4 (2020): 1808–13. http://dx.doi.org/10.21275/sr24314131459.

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Prince, Singla, and Singla Rupinder. "Detection of Aged Bloodstains by using Different Techniques- A Review." Detection of Aged Bloodstains by using Different Techniques- A Review 8, no. 10 (2023): 4. https://doi.org/10.5281/zenodo.10026378.

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With an increase in criminal activities, a large number of crime cases are reported every day. These violent crimes are usually suicidal, homicidal, or accidental in nature. In forensics investigations, blood is the most significant and valuable biological evidence, which is found very frequently at crime scene. The main motive of the collection of biological samples from the crime scenes is to get the genetic information from collected samples and use that information for the identification of the suspect. A DNA profile indicates the person's identity and the pattern of the streaks reveals th

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B, Meena Preethi, Sunitha C, Parameshvar M, Dharshini B, and Gokul S. "Emotion Detection using HOG for Crime Detection." Indian Journal of Science and Technology 16, no. 41 (2023): 3617–26. https://doi.org/10.17485/IJST/v16i41.1580.

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Abstract <strong>Objectives:</strong> The main objective of this study is to develop an advanced emotion detection system that can contribute to crime detection and prevention efforts. By using the power of machine learning, the system aims to enhance the effectiveness in identifying potential criminal activities by analyzing emotional cues of people. <strong>Methods:</strong> The proposed method is evaluated using Facial Expression Recognition – 2013 (FER – 2013) dataset from a Kaggle data science community. It consists of 3589 training data files with 48x48 pixel g

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B, Meena Preethi, Sunitha C, Parameshvar M, Dharshini B, and Gokul S. "Emotion Detection using HOG for Crime Detection." Indian Journal of Science and Technology 16, no. 41 (2023): 3617–26. https://doi.org/10.17485/IJST/v16i41.1580.

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Abstract <strong>Objectives:</strong> The main objective of this study is to develop an advanced emotion detection system that can contribute to crime detection and prevention efforts. By using the power of machine learning, the system aims to enhance the effectiveness in identifying potential criminal activities by analyzing emotional cues of people. <strong>Methods:</strong> The proposed method is evaluated using Facial Expression Recognition – 2013 (FER – 2013) dataset from a Kaggle data science community. It consists of 3589 training data files with 48x48 pixel g

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B, Meena Preethi, Sunitha C, Parameshvar M, Dharshini B, and Gokul S. "Emotion Detection using HOG for Crime Detection." Indian Journal of Science and Technology 16, no. 41 (2023): 3617–26. https://doi.org/10.17485/IJST/v16i41.1580.

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Abstract <strong>Objectives:</strong> The main objective of this study is to develop an advanced emotion detection system that can contribute to crime detection and prevention efforts. By using the power of machine learning, the system aims to enhance the effectiveness in identifying potential criminal activities by analyzing emotional cues of people. <strong>Methods:</strong> The proposed method is evaluated using Facial Expression Recognition – 2013 (FER – 2013) dataset from a Kaggle data science community. It consists of 3589 training data files with 48x48 pixel g

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B, Meena Preethi, Sunitha C, Parameshvar M, Dharshini B, and Gokul S. "Emotion Detection using HOG for Crime Detection." Indian Journal of Science and Technology 16, no. 41 (2023): 3617–26. https://doi.org/10.17485/IJST/v16i41.1580.

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Abstract:

Abstract <strong>Objectives:</strong> The main objective of this study is to develop an advanced emotion detection system that can contribute to crime detection and prevention efforts. By using the power of machine learning, the system aims to enhance the effectiveness in identifying potential criminal activities by analyzing emotional cues of people. <strong>Methods:</strong> The proposed method is evaluated using Facial Expression Recognition – 2013 (FER – 2013) dataset from a Kaggle data science community. It consists of 3589 training data files with 48x48 pixel g

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B, Meena Preethi, Sunitha C, Parameshvar M, Dharshini B, and Gokul S. "Emotion Detection using HOG for Crime Detection." Indian Journal of Science and Technology 16, no. 41 (2023): 3617–26. https://doi.org/10.17485/IJST/v16i41.1580.

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Abstract:

Abstract <strong>Objectives:</strong> The main objective of this study is to develop an advanced emotion detection system that can contribute to crime detection and prevention efforts. By using the power of machine learning, the system aims to enhance the effectiveness in identifying potential criminal activities by analyzing emotional cues of people. <strong>Methods:</strong> The proposed method is evaluated using Facial Expression Recognition – 2013 (FER – 2013) dataset from a Kaggle data science community. It consists of 3589 training data files with 48x48 pixel g

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Gupta, Gautam, Prachi Aggarwal, Achin Jain, Puneet Singh Lamba, Arun Kumar Dubey, and Gopal Chaudhary. "Crime Anomaly Detection using CNN and Ensemble Model." Fusion: Practice and Applications 11, no. 1 (2023): 89–99. http://dx.doi.org/10.54216/fpa.110107.

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Every single day, thousands of crimes are perpetrated, and hundreds may be probably taking place right now throughout the world. Without a doubt, crime is viewed as a social blight. Nothing can truly stop it, no matter what is done. Surveillance cameras, on the other hand, can dramatically minimize it. Using public surveillance camera systems to prevent, document, and minimize crime can be a cost-effective solution. Installing enough cameras to detect crimes in progress and integrating technology to automate the monitoring of the live stream from these cameras will result in the most effective

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Sharov, Viktor, and Andrey Diaghilev. "Scientific theories of detecting and solving crimes." Legal Science and Practice: Journal of Nizhny Novgorod Academy of the Ministry of Internal Affairs of Russia 2022, no. 4 (2022): 179–85. http://dx.doi.org/10.36511/2078-5356-2022-4-179-185.

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Operational-investigative activity (hereinafter — ORD) rightfully occupies one of the leading places in the fight against crime, especially with its hidden, non-obvious forms. The main content of the practical OSA is the processes of detecting and solving crimes, documenting criminal activities. In turn, the main task of the theory of ORD is the scientific support of the practical activity of the same name. This manifests the dialectical relationship between operational-search theory and practice. Within the framework of the presented article, an attempt was made to consider scientific approac

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ISLAMAJ, Visar. "PSYCHOLOGICAL METHODOLOGY OF CRIME DETECTION (ZIGMUND FREUD ON CRIME)." International Journal of Legal Sciences-JUSTICIA 12, no. 21-22 (2024): 278–82. http://dx.doi.org/10.62792/ut.jus.v12.i21-22.p2780.

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Sigmund Freud is recognized worldwide as the original psychoanalyst founded to form theories and concepts surrounding the existence of mental illness and its nature in relation to human behavior. Throughout his psychological and psychoanalytic studies, Freud concluded that behavior can be explained through the investigation of one's experiences and traumas by accounting for the motivation of a person's actions. Interpretation of his findings concluded that a person can adapt his/her behavior from childhood experiences to become part of the hidden state of consciousness He studied unobservable

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Gottschalk, Petter. "Filling the Gap in White-Collar Crime Detection Between Government and Governance: The Role of Investigative Journalists and Fraud Examiners." Journal of White Collar and Corporate Crime 2, no. 1 (2020): 36–46. http://dx.doi.org/10.1177/2631309x20925818.

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This article suggests that investigative journalists in the media and fraud examiners in private investigations have the potential of filling some of the detection gap. Based on the theory of crime signal detection, this article suggests that investigative journalists are in the position of detecting white-collar crime scandals as they rely on tips and whistleblowing. Empirical evidence from Norway documents that the media disclose a significant fraction of crime stories that later result in prosecution and conviction of white-collar offenders. Empirical evidence from Norway does not document

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KELMENDI, Magbule. "WHITE COLLAR CRIME AS ORGANIZED INSTITUTIONAL CRIME." International Journal of Legal Sciences-JUSTICIA 12, no. 21-22 (2024): 100–105. http://dx.doi.org/10.62792/ut.jus.v12.i21-22.p2759.

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The object of treatment in this paper is the problem of detection and treatment of corruption. There is no single definition for corruption and in this case it is limited to the corruption practices of white-collar crime, being a link to institutional organized crime, with confirmation of the suspicion of crime in the Prosecutor's Office - especially that of serious crimes which is the main pillar of the state in this right to enforce the law and fight the phenomenon, as well as the state courts. Its meaning is broad and cannot be defined only by accepting or giving a bribe to an official or b

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Tsybulsky, V. V. "METHODOLOGICAL BASES OF INVESTIGATION OF CORRUPTION CRIMES COMMITTED BY TRAFFIC POLICE OFFICERS." Bulletin of Udmurt University. Series Economics and Law 31, no. 4 (2021): 711–16. http://dx.doi.org/10.35634/2412-9593-2021-31-4-711-716.

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Corruption crimes committed by traffic police officers have features that distinguish them from other corruption crimes. These features are important for solving the issue of effective detection and investigation of crimes of this type. At the same time, special attention in the investigation should be paid to how traffic police officers use official powers granted to them by law, as well as to what subjective rights are granted as a result of their abuse of these powers. It is noteworthy that the official powers act in the course of committing corruption crimes by traffic police officers as a

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Bac, Mehmet. "Crime Chains." American Economic Journal: Microeconomics 14, no. 4 (2022): 680–722. http://dx.doi.org/10.1257/mic.20200314.

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How should law enforcement resources be allocated to minimize the harms from flexible, chain-form trafficking organizations? I show that optimal interventions focus on one target, the feeding source (decapitation) or the revenue-generating tail (amputation). Decapitation dismantles the crime chain under large budgets but induces maximal expansion otherwise, whereas amputation generates a rich set of detection outcomes and limits the chain’s size response. A rule of thumb emerges for authorities to target tail segments under small budgets and high detection contiguity, qualified by chain profit

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Li, Gang, and Yong Wen. "Research on the Detection Countermeasures of Telecommunication Network Fraud Based on Big Data for Killing Pigs and Plates." Journal of Robotics 2022 (March 7, 2022): 1–11. http://dx.doi.org/10.1155/2022/4761230.

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This paper uses big data analysis to conduct in-depth analysis and research on the investigation countermeasures of the pig-killing dish telecommunication network fraud. This paper takes the case of “piggy bank” as a perspective, starting from analyzing the concept and characteristics of “piggy bank” type network fraud, analyzing the current phenomenon of this type of network fraud crime, and analyzing the current situation of the relevant laws, to explore the judicial situation regarding this type of network fraud crime, and to explore the problems and dilemmas in the judicial determination o

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Ocieczek, Grzegorz. "Combating Organised Economic Crime in Poland: Statistical and Organisational Aspects." Central European Journal of Comparative Law 4, no. 1 (2023): 73–90. http://dx.doi.org/10.47078/2023.1.73-90.

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The subject of the article is to discuss the determinants of economic crime in Poland from a criminal law perspective. The author discusses the characteristics of the issue and the genesis of organized crime in Poland. He presents statistics that discuss the activities of criminal groups and the development of economic crime in Poland. The text discusses important issues from the perspective of the prosecution of the crimes in question and the role and position of selected legal protection authorities. The author points out the strengths and weaknesses of the Polish system for combating econom

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