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.

Bibliographic Details
Main Authors:	Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Other Authors:	Mostakim, Moin
Format:	Thesis
Language:	English
Published:	Brac University 2023
Subjects:	Neural network Object detection Conveyor belt VGG16 ResNet MobileNet YOLOv5 YOLOv7 Convolutional Neural Network CNN Vision transformer Neural networks (Computer science)
Online Access:	http://hdl.handle.net/10361/19296

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