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

Internet

http://hdl.handle.net/10361/22038

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