Crime Prediction Using Deep Learning 015951 Pdf This review paper examines over 150 articles to explore the various machine learning and deep learning algorithms applied to predict crime. The document proposes developing an intelligent crime detection system using deep learning to monitor cctv footage and detect crimes without human involvement. it would use the ucf crime dataset containing 1900 surveillance videos to train a model to recognize abnormalities like fights, accidents, burglaries and raise alarms.
Crime Prediction Using Machine Learning And Deep Learning A Systematic This review paper examines over 150 articles to explore the various machine learning and deep learning algorithms applied to predict crime. the study provides access to the datasets used. The study provides access to the datasets used for crime prediction by researchers and analyzes prominent approaches applied in machine learning and deep learning algorithms to predict crime, offering insights into different trends and factors related to criminal activities. Based on the recent advances in this field [1], [2] [3], this article will explore current trends in machine learning and deep learning for crime prediction and discuss how these cutting edge technologies are being used to detect criminal activities, predict crime patterns, and prevent crime. Deep learning techniques have demonstrated remarkable potential in analysing various types of data sources, such as surveillance footage, sensor data, and social media feeds, to identify criminal activities, predict incidents, and aid law enforcement agencies in proactive responses.
Crime Detection Using Deep Learning Regression Techniques Download Based on the recent advances in this field [1], [2] [3], this article will explore current trends in machine learning and deep learning for crime prediction and discuss how these cutting edge technologies are being used to detect criminal activities, predict crime patterns, and prevent crime. Deep learning techniques have demonstrated remarkable potential in analysing various types of data sources, such as surveillance footage, sensor data, and social media feeds, to identify criminal activities, predict incidents, and aid law enforcement agencies in proactive responses. Exploratory data analysis predicts more than 35 crime types and suggests a yearly decline in chicago crime rate, and a slight increase in los angeles crime rate; with fewer crimes. Utilizing a comprehensive dataset of historical crime incidents, we assess various deep learning architectures alongside random forest to evaluate their predictive capabilities. our results demonstrate significant improvements in prediction accuracy, providing actionable insights for law enforcement agencies. Deep learning based crime prediction models use complex architectures to capture the latent features in the crime data, and outperform the statistical and classical machine learning based crime prediction methods. Crime prediction is a complex problem requiring advanced analytical tools to effectively address the gaps in existing detection mechanisms.
Pdf Crime Prediction Using Machine Learning And Deep Learning A Exploratory data analysis predicts more than 35 crime types and suggests a yearly decline in chicago crime rate, and a slight increase in los angeles crime rate; with fewer crimes. Utilizing a comprehensive dataset of historical crime incidents, we assess various deep learning architectures alongside random forest to evaluate their predictive capabilities. our results demonstrate significant improvements in prediction accuracy, providing actionable insights for law enforcement agencies. Deep learning based crime prediction models use complex architectures to capture the latent features in the crime data, and outperform the statistical and classical machine learning based crime prediction methods. Crime prediction is a complex problem requiring advanced analytical tools to effectively address the gaps in existing detection mechanisms.