Camera-Based Crime Behavior Detection and Classification
Highlights
- An efficient crime detection system based on deep learning multi-model integration accurately detects arson, burglary, and vandalism.
- Optimal models and ensemble techniques enhance detection accuracy, robustness, and generalization.
- An automated crime identification system with real-time SMS alerts can improve the effectiveness of crime prevention.
- A Gradio-based web system integrated with Twilio facilitates user alert management and customization.
Abstract
Share and Cite
Gao, J.; Shi, J.; Balla, P.; Sheshgiri, A.; Zhang, B.; Yu, H.; Yang, Y. Camera-Based Crime Behavior Detection and Classification. Smart Cities 2024, 7, 1169-1198. https://doi.org/10.3390/smartcities7030050
Gao J, Shi J, Balla P, Sheshgiri A, Zhang B, Yu H, Yang Y. Camera-Based Crime Behavior Detection and Classification. Smart Cities. 2024; 7(3):1169-1198. https://doi.org/10.3390/smartcities7030050
Chicago/Turabian StyleGao, Jerry, Jingwen Shi, Priyanka Balla, Akshata Sheshgiri, Bocheng Zhang, Hailong Yu, and Yunyun Yang. 2024. "Camera-Based Crime Behavior Detection and Classification" Smart Cities 7, no. 3: 1169-1198. https://doi.org/10.3390/smartcities7030050