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Crime Cctv Image Detection
An image classification model based on Google Vision Transformer (ViT) architecture for detecting criminal activities in surveillance camera images, with approximately 83% accuracy.
Downloads 117
Release Time : 11/2/2024
Model Overview
This model is specifically designed to analyze surveillance camera footage and automatically identify potential criminal activities. Implemented using ViT architecture for efficient image classification, suitable for public security applications.
Model Features
High-Accuracy Crime Detection
Achieves 82.64% accuracy on test dataset with F1 score of 0.8262
ViT-Based Architecture
Utilizes Vision Transformer architecture, well-suited for image classification tasks
Real-time Surveillance Support
Suitable for real-time analysis of surveillance camera footage
Model Capabilities
Image Classification
Criminal Activity Recognition
Surveillance Video Analysis
Use Cases
Public Safety
Real-time Crime Monitoring
Deployed in surveillance systems to automatically detect suspicious activities
Helps security personnel promptly identify potential criminal activities
Historical Footage Analysis
Batch analysis of stored surveillance footage to search for criminal evidence
Improves efficiency of evidence collection
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