Leveraging robust CNN architectures for real-time object recognition from conveyor belt

Leveraging robust CNN architectures for real-time object recognition from conveyor belt

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

Opis bibliograficzny
Główni autorzy: Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Kolejni autorzy: Mostakim, Moin
Format: Praca dyplomowa
Język:English
Wydane: Brac University 2023
Hasła przedmiotowe:
Neural network
Object detection
Conveyor belt
VGG16
ResNet
MobileNet
YOLOv5
YOLOv7
Convolutional Neural Network
CNN
Vision transformer
Neural networks (Computer science)
Dostęp online:http://hdl.handle.net/10361/19296

Internet

http://hdl.handle.net/10361/19296

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