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.

Détails bibliographiques
Auteurs principaux: Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Autres auteurs: Mostakim, Moin
Format: Thèse
Langue:English
Publié: Brac University 2023
Sujets:
Neural network
Object detection
Conveyor belt
VGG16
ResNet
MobileNet
YOLOv5
YOLOv7
Convolutional Neural Network
CNN
Vision transformer
Neural networks (Computer science)
Accès en ligne:http://hdl.handle.net/10361/19296

Internet

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

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