Real-time crime detection using convolutional LSTM and YOLOv7

Real-time crime detection using convolutional LSTM and YOLOv7

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Bibliografiska uppgifter
Huvudupphovsmän:	Sakiba, Cyrus, Tarannum, Syeda Maisha, Nur, Farzana, Arpan, Fahad Faisal, Anzum, Ahnaf Ahmed
Övriga upphovsmän:	Rahman, Md. Khalilur
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2023
Ämnen:	Deep learning Bidirectional LSTM YOLOv7 YOLOv4 MobilenetV2 Violence prediction Realtime Machine learning Cognitive learning theory Real-time data processing
Länkar:	http://hdl.handle.net/10361/22038

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