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.

Dades bibliogràfiques
Autors principals: Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Altres autors: Mostakim, Moin
Format: Thesis
Idioma:English
Publicat: Brac University 2023
Matèries:
Neural network
Object detection
Conveyor belt
VGG16
ResNet
MobileNet
YOLOv5
YOLOv7
Convolutional Neural Network
CNN
Vision transformer
Neural networks (Computer science)
Accés en línia:http://hdl.handle.net/10361/19296

Internet

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

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