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.

Bibliographische Detailangaben
Hauptverfasser:	Sakiba, Cyrus, Tarannum, Syeda Maisha, Nur, Farzana, Arpan, Fahad Faisal, Anzum, Ahnaf Ahmed
Weitere Verfasser:	Rahman, Md. Khalilur
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2023
Schlagworte:	Deep learning Bidirectional LSTM YOLOv7 YOLOv4 MobilenetV2 Violence prediction Realtime Machine learning Cognitive learning theory Real-time data processing
Online Zugang:	http://hdl.handle.net/10361/22038

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