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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς:	Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Άλλοι συγγραφείς:	Mostakim, Moin
Μορφή:	Thesis
Γλώσσα:	English
Έκδοση:	Brac University 2023
Θέματα:	Neural network Object detection Conveyor belt VGG16 ResNet MobileNet YOLOv5 YOLOv7 Convolutional Neural Network CNN Vision transformer Neural networks (Computer science)
Διαθέσιμο Online:	http://hdl.handle.net/10361/19296

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