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Littérature scientifique sur le sujet « Crime hotspot »

Auteur : Grafiati

Publié le 2 juin 2025

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Crime hotspot"

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Ajide, Oyinloye M., and Olamiju I. Oluwadare. "Mapping Crime Hotspots in Akure, Nigeria: A GIS Perspective." Urban Studies and Public Administration 1, no. 1 (2018): 135. http://dx.doi.org/10.22158/uspa.v1n1p135.

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<p><em>African countries in recent times have witnessed an unprecedented level of insecurity. This has made national security threat to be a major issue for the government and has prompted huge allocation of the national budget to security. The objective of this paper is to mark out crime hotspot areas in the central area of Akure metropolis; and examine the rate at which crimes are committed, the surveillance method used and its effectiveness. The research made use of Google Earth imagery and Geographical Information System (GIS) technology to delineate crime hotspots in Akure. A

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Hart, Timothy C. "Investigating Crime Pattern Stability at Micro-Temporal Intervals: Implications for Crime Analysis and Hotspot Policing Strategies." Criminal Justice Review 46, no. 2 (2021): 173–89. http://dx.doi.org/10.1177/0734016821996785.

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Studies of crime hotspot forecasts use various metrics to describe different characteristics of prediction patterns. However, few investigations consider how the stability of crime hotspot, estimated at relatively short temporal intervals, can impact hotspot policing efforts. In response, using address-level incident location data that were collected from six law enforcement agencies in the United States, the current study examines the daily stability of crime hotspots that were estimated over a 1-year period. Results suggest that micro-temporal stability patterns in crime hotspot forecasts ar

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He, Zhanjun, Rongqi Lai, Zhipeng Wang, Huimin Liu, and Min Deng. "Comparative Study of Approaches for Detecting Crime Hotspots with Considering Concentration and Shape Characteristics." International Journal of Environmental Research and Public Health 19, no. 21 (2022): 14350. http://dx.doi.org/10.3390/ijerph192114350.

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Hotspot detection is an important exploratory technique to identify areas with high concentrations of crime and help deploy crime-reduction resources. Although a variety of methods have been developed to detect crime hotspots, few studies have systematically evaluated the performance of various methods, especially in terms of the ability to detect complex-shaped crime hotspots. Therefore, in this study, a comparative study of hotspot detection approaches while simultaneously considering the concentration and shape characteristics was conducted. Firstly, we established a framework for quantitat

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Mei, Linfeng, and Juncheng Wei. "The existence and stability of spike solutions for a chemotax is system modeling crime pattern formation." Mathematical Models and Methods in Applied Sciences 30, no. 09 (2020): 1727–64. http://dx.doi.org/10.1142/s0218202520500359.

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Urban crime such as residential burglary is a social problem in every major urban area. As such, many mathematical models have been proposed to study the collective behavior of these crimes. In [V. B. Pasour, G. E. Tita, P. J. Brantingham, A. L. Bertozzi, M. B. Short, M. R. D’Orsogna and L. B. Chayes, A statistical model of crime behavior, Math. Methods Appl. Sci 107 (2008) 1249–1267; M. B. Short, A. L. Bertozzi and P. J. Brantingham, Nonlinear patterns in urban crime: Hotspots, bifurcations, and suppression, SIAM J. Appl. Dyn. Syst. 9 (2010) 462–483], Short et al. proposed an agent-based stat

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Soppari, Dr Kavitha. "City Crime Hotspot Identification and Visualization Development of a Web Application for Improving Urban Safety and Decision Making." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03400.

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Abstract: Urban crime hotspots present significant challenges to public safety and effective city planning. This study proposes a web-based crime hotspot identification and visualization system that utilizes geospatial mapping, machine learning, and data analytics. The application empowers law enforcement agencies and policymakers by classifying high-risk areas, tracking evolving crime trends, and predicting future crime occurrences. The system’s interactive dashboard delivers real-time, data-driven insights to support strategic decision-making and improve urban safety outcomes. Keywords: Crim

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Debata, Ipsita, Prem Sagar Panda, E. Karthikeyan, et al. "Spatial auto-correlation and endemicity pattern analysis of crimes against children in Tamil Nadu from 2017 to 2021." Journal of Family Medicine and Primary Care 13, no. 6 (2024): 2341–47. http://dx.doi.org/10.4103/jfmpc.jfmpc_1463_23.

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ABSTRACT Background: A child is a nation’s supreme asset and future. India homes 444 million children, aged between 0 and 18 years, contributing to 19% of the world’s children. Crime against children is detrimental to their mental and physical health and affects their growth and development. The National Crime Record Bureau recently reported that a crime targeting children happens every 4 minutes. There is a paucity of literature regarding the burden of crime against children. To understand the magnitude and spatial distribution of crime against children, a retrospective surveillance study was

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Chainey, Spencer P., Sophie J. Curtis-Ham, R. Mark Evans, and Gordon J. Burns. "Examining the extent to which repeat and near repeat patterns can prevent crime." Policing: An International Journal 41, no. 5 (2018): 608–22. http://dx.doi.org/10.1108/pijpsm-12-2016-0172.

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Purpose The purpose of this paper is to examine the extent and variation in the estimates to which crime can be prevented using patterns of repeats and near repeats, and whether hotspot analysis complements these patterns. Design/methodology/approach Crime data for four study areas in New Zealand are used to examine differences in the extent of burglary repeat and near repeat victimisation. Hotspots of burglary are also created to determine the extent to which burglary repeats and near repeats spatially intersect hotspots. Findings The extent of repeats and near repeats varies, meaning there i

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Rajapandian, Mr P. "Enhanced Crime Hotspot Prediction and Visualization for Women’s Safety Through Deep Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49726.

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Abstract- Crime hotspots are geographic areas with elevated levels of criminal activities compared to other regions. Women in these hotspots are at increased risk of experiencing various forms of criminal behavior, including sexual harassment, assault, domestic violence, stalking, and human trafficking. Identifying these hotspots is crucial for effective crime prevention and resource allocation by law enforcement agencies. This project presents Safety Locator, a predictive system that uses multimodal deep learning to identify and map crime hotspots where women are particularly vulnerable. The

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Nakamura, Hiroki, and Shunsuke Managi. "Why does perceive safety endure in crime hotspots? Case of Delhi." Safer Communities 19, no. 4 (2020): 183–98. http://dx.doi.org/10.1108/sc-02-2020-0006.

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Purpose Using a case study from Delhi, India, this study aims to investigate why perceived safety endures despite crimes in the neighborhood. Local residents in Delhi feel considerably less fearful of crime in their neighborhoods, and a majority reported feeling safe in their neighborhoods, especially during the daytime. Design/methodology/approach This paper hypothesized that similar to the crime itself, perceptions of safety or the fear of crime, also tend to be concentrated in hotspots. Following a hotspot analysis based on the respondents’ perceptions of safety, the data gathered were appl

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Redzuan, Mohd Sofian, Tarmiji Masron, Syahrul Nizam Junaini, et al. "Urban Violent Crime Dynamics in Kuala Lumpur and Putrajaya: Utilizing Spatial Temporal Techniques." Forum Geografi 39, no. 1 (2025): 1–19. https://doi.org/10.23917/forgeo.v39i1.6456.

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This paper investigates the patterns of violent crime in Kuala Lumpur and Putrajaya between 2015 and 2020 using advanced spatial analysis techniques, including Spatial Autocorrelation, Standard Deviational Ellipse (SDE), and Mean Centre (MC). The study analyses the spatial distribution and temporal dynamics of violent crimes, tracks shift in crime hotspots and examines the influence of socio-economic factors on these patterns. Findings reveal that violent crimes predominantly occurred in the late afternoon and night, with peak incidents at 3:00 PM (1,830 cases, 8.28%). The study highlights not

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Thèses sur le sujet "Crime hotspot"

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Hussein, Abdul Aziz. "Identifying Crime Hotspot: Evaluating the suitability of Supervised and Unsupervised Machine learning." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1624914607243042.

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Chainey, S. "Examining the extent to which hotspot analysis can support spatial predictions of crime." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1458643/.

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The premise that where crime has occurred previously, informs where crime is likely to occur in the future has long been used for geographically targeting police and public safety services. Hotspot analysis is the most applied technique that is based on this premise – using crime data to identify areas of crime concentration, and in turn predict where crime is likely to occur. However, the extent to which hotspot analysis can accurately predict spatial patterns of crime has not been comprehensively examined. The current research involves an examination of hotspot analysis techniques, measuring

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Wang, Ninghua. "Analyzing spatial effects of hotspot policing with a simulation approach." University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1245164864.

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Zugschwerdt, Marc. "'Designing out Crime' – A Spatial and Temporal Analysis of Crime in Umeå." Thesis, Umeå universitet, Kulturgeografi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-137192.

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The creation of sustainable and safe environments nowadays moves more and more into focus for urban planners and architects. Cities should be designed in a way to contribute to social cohesion, shaping an inclusive environment and focusing on the wellbeing of its citizens. Nevertheless, these processes can be undermined by public crime and the fear of crime, which is not only affecting aspects of personal safety but also affecting the people’s behaviour. Reasons why criminality occurs are manifold, impacted by a dynamic set of socioeconomic, demographic, personal but also environmental aspects

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Childs, Lauren. "A New Orleans State of Crime: Spatio-Temporal Analysis of Shifting Homicide Patterns In Post-Hurricane Katrina New Orleans, LA." ScholarWorks@UNO, 2009. http://scholarworks.uno.edu/td/974.

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Dubbed the "most murderous" and "deadliest" city in the United States during 2006, 2007 and 2008, New Orleans has wrestled with crime and murder since its founding in 1718. Following Hurricane Katrina the city saw an increase in the murder rate despite a sharp decrease in population. The focus of this project was to map homicide data trends in the city of New Orleans over a period of seven years, 2002 to 2008, and compare spatial and temporal patterns via GIS. NOPD homicide location data were geocoded and analyzed in ESRI's ArcGIS geospatial software. Methodologies of hotspot detection inclu

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Fransson, Axel, and Mårtensson Lukas Ramhorn. "Geografiska informationssystem, ett effektivt IT-stöd för polisen." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20292.

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Studien syftar till att undersöka hur den svenska polismyndigheten använder sig av Geografiska informationssystem (GIS). Den digitala förändringen är intensiv vilket leder till möjligheter och utmaningar gällande den brottsbekämpning som råder i Sverige. För att vara följsam i den förändring som sker behövs det nya och fler effektiva metoder. GIS inom polisen är förekommande i länder som bland annat USA, England och Nederländerna, medan Sveriges arbete med GIS inom polismyndigheten är allt mer diffust. De slutsatser som har kunnat dras är att GIS kan innebära stora möjligheter för polisen, de

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Barrett, Kimberly L. "Assessing the Relationship Between Hotspots of Lead and Hotspots of Crime." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4435.

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Numerous medical and environmental toxicology studies have established a link between lead (Pb) exposure, crime, and delinquency. In human environments, lead pollution- like crime- is unequally distributed, creating lead hot spots. In spite of this, studies of crime hotspots have routinely focused on traditional sociological predictors of crime, leaving environmental predictors of crime like lead and other neurotoxins relatively unaddressed. This study attends to this gap in the literature by asking a very straightforward research question: Is there a relationship between hotspots of lead an

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MADENSEN, TAMARA D. "BAR MANAGEMENT AND CRIME: TOWARD A DYNAMIC THEORY OF PLACE MANAGEMENT AND CRIME HOTSPOTS." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1180461844.

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Madensen, Tamara D. "Bar management and crime toward a dynamic theory of place management and crime hotspots /." Cincinnati, Ohio : University of Cincinnati, 2007. http://www.ohiolink.edu/etd/view.cgi?ucin1180461844.

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Johansson, Erik, and Christoffer Gåhlin. "Crime hotspots: An evaluation of the KDE spatial mapping technique : Spatial analysis." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-678.

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Context Crime rates are increasing more and more, especially residential burglaries. This thesis includes a study of the Kernel Density Estimation algorithm, and how to use this algorithm for mapping crime patterns based on geographical data. By visualizing patterns as spatial hotspots, law-enforcements can get a better understanding of how criminals think and act. Objectives The thesis focuses on two experiments, including measuring the accuracy and performance of the KDE algorithm, as well as the analysis of the amount of crime data needed to compute accurate and reliable results. Methods

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Livres sur le sujet "Crime hotspot"

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Commission, Virginia State Crime. Hotspot communities: Report of the Virginia State Crime Commission to the Governor and the General Assembly of Virginia. Commonwealth of Virginia, 2000.

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van Uhm, Daan. Organized Environmental Crime. Bloomsbury Publishing Inc, 2023. http://dx.doi.org/10.5040/9798216172185.

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Developing an innovative approach to understanding how organized crime groups diversify into the illegal trade in natural resources, this book looks at the convergence between environmental crime and other serious crimes. In Organized Environmental Crime, Daan van Uhm breaks new ground by rejecting the classic image of organized crime as specializing in one kind of criminal activity. Instead, he develops an innovative approach to understanding how organized crime groups diversify into the illegal trade in natural resources by looking at the convergence between environmental crime and other ser

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Newton, Andrew. Macro-Level Generators of Crime, Including Parks, Stadiums, and Transit Stations. Edited by Gerben J. N. Bruinsma and Shane D. Johnson. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190279707.013.16.

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This chapter examines the occurrence of crime at particular places that bring together lots of people in time and place, namely macro crime generators. Examples of these include hospitals, parks, large transit stations and interchanges, entertainment districts, and shopping malls. It begins by defining crime attractors and crime generators, and explores the subtle difference between them. It then examines why crime hotspots and crime generators tend to coexist, and considers the importance of scale in place-based studies of crime. Following this is a discussion of the “busyness” of crime gener

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Nault, Derrick M. Africa and the Shaping of International Human Rights. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198859628.001.0001.

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Africa throughout its postcolonial history has been plagued by human rights abuses ranging from intolerance of political dissent to heinous crimes such as genocide. Some observers consequently have gone so far as to suggest that human rights are a concept alien to African cultures. The International Criminal Court (ICC)’s focus on Africa in recent years has reinforced the region’s reputation as a hotspot for human rights violations. But despite Africa’s notoriety concerning human rights, Africa and the Shaping of International Human Rights argues that the continent has been pivotal for helping

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Chapitres de livres sur le sujet "Crime hotspot"

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Kurland, Justin, Nick Tilley, and Shane D. Johnson. "The Football ‘Hotspot’ Matrix." In Football Hooliganism, Fan Behaviour and Crime. Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137347978_2.

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Nair, Sankar N., and E. S. Gopi. "Deep Learning Techniques for Crime Hotspot Detection." In Algorithms for Intelligent Systems. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0994-0_2.

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Ibrahim, Suleiman, Paresh Jain, Mukesh Bhardwaj, Mukesh Kumar Gupta, and Mukesh Kumar Bansal. "Predictive Crime Hotspot Detection: A Spatial Analysis Approach." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1946-4_26.

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Cheng, Tao, and Tongxin Chen. "Urban Crime and Security." In Urban Informatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_14.

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AbstractScientists have an enduring interest in understanding urban crime and developing security strategies for mitigating this problem. This chapter reviews the progress made in this topic from historic criminology to data-driven policing. It first reviews the broad implications of urban security and its implementation in practice. Next, it focuses on the tools to prevent urban crime and improve security, from analytical crime hotspot mapping to police resource allocation. Finally, a manifesto of data-driven policing is proposed, with its practical demand for efficient security strategies an

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Tabarej, Mohd Shamsh, and Sonajharia Minz. "Change Footprint Pattern Analysis of Crime Hotspot of Indian Districts." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3383-9_30.

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Wolff, Markus, and Hartmut Asche. "Geospatial Crime Scene Investigation – From Hotspot Analysis to Interactive 3D Visualization." In Computational Science and Its Applications – ICCSA 2009. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02454-2_20.

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Gulati, Medha, Arpita Rajpoot, Chahak Gautam, and K. R. Seeja. "A Novel Spatio-Temporal Model for Crime Hotspot Identification and Prediction." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0838-7_40.

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Naik, Archana, Aakanksha Gaur, Stuti Srivastava, Shashikant Saini, R. Gayathri, and Kavitha Sooda. "Rakshak—Prototype Application to Depict Crime Hotspot and Safest Path Between Locations." In Computer Networks, Big Data and IoT. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0898-9_1.

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Chandna, Kumar Rai, and Premal Patel. "An Analysis of Hotspot Policing Pattern to Effectively Address the Crime and Disorder." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-6681-9_51.

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Chainey, Spencer, and Jerry Ratcliffe. "Identifying Crime Hotspots." In GIS and Crime Mapping. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118685181.ch6.

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Actes de conférences sur le sujet "Crime hotspot"

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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.

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Pawar, Rohan, and I. R. Praveen Joe. "Smart Alarm System for Crime Hotspot Detection using Deep Learning." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10724960.

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Roshankar, Rojan, and Mohammad Reza Keyvanpour. "STANet: Spatio-Temporal Attention-Enhanced WaveNet for Crime Hotspot Prediction." In 2024 15th International Conference on Information and Knowledge Technology (IKT). IEEE, 2024. https://doi.org/10.1109/ikt65497.2024.10892754.

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Dubey, Aditya, Nookala Venu, Dhananjay Bisen, Priyanka Garg, Kande Srinivas, and Hemlata Arya. "A Clustering-Based Method for Hotspot Recognition in Crime Forecasting." In 2024 IEEE 8th International Conference on Information and Communication Technology (CICT). IEEE, 2024. https://doi.org/10.1109/cict64037.2024.10899713.

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Lilhare, Shweta G., Yash Kumavat, Gunwant Banait, and Aditya Kurkelli. "Crime Hotspots Mapping and FIR Data Interface." In 2024 International Conference on Innovations and Challenges in Emerging Technologies (ICICET). IEEE, 2024. http://dx.doi.org/10.1109/icicet59348.2024.10616366.

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Keerthika, V., A. Geetha, and D. M. Deepak Raj. "Predictive Crime Analysis: Statistical Approach to Forecast Crime Hotspots Using Recursive Neural Network in Deep Learning." In 2024 Second International Conference on Advances in Information Technology (ICAIT). IEEE, 2024. http://dx.doi.org/10.1109/icait61638.2024.10690551.

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Ahamed, Shaik Sardar Zubair, Sokkam Chaitra Sree, Shaik Sanugondla Dada Khalindar, Pochireddy Dharmaja, and V. V. Satyanarayana Tallapragada. "Prediction of Crime Hotspots using Machine Learning with Stacked Generalized Approach." In 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2024. http://dx.doi.org/10.1109/icacite60783.2024.10617071.

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Neelambaram, B., M. Sunil Kumar, D. Ganesh, A. V. Raghuram, M. ShyamSundar, and Tej Prakash Uppu. "Analysis and Prediction of Crime Hotspots Using Machine Learning With Stacked Generalization Approach." In 2024 International Conference on Computational Intelligence for Green and Sustainable Technologies (ICCIGST). IEEE, 2024. http://dx.doi.org/10.1109/iccigst60741.2024.10717502.

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Borges, Julio, Daniel Ziehr, Michael Beigl, et al. "Feature engineering for crime hotspot detection." In 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2017. http://dx.doi.org/10.1109/uic-atc.2017.8397586.

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Bogucki, Robert, Jan Kanty Milczek, and Patryk Miziuła. "A simple crime hotspot forecasting algorithm." In 2020 Federated Conference on Computer Science and Information Systems. IEEE, 2020. http://dx.doi.org/10.15439/2020f5.

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Rapports d'organisations sur le sujet "Crime hotspot"

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Blattman, Christopher, Donald Green, Daniel Ortega, and Santiago Tobón. Hotspot interventions at scale: the effects of policing and city services on crime in Bogotá, Colombia. International Initiative for Impact Evaluation (3ie), 2018. http://dx.doi.org/10.23846/dpw1ie88.

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