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.

Dettagli Bibliografici
Autori principali: Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Altri autori: Mostakim, Moin
Natura: Tesi
Lingua:English
Pubblicazione: Brac University 2023
Soggetti:
Neural network
Object detection
Conveyor belt
VGG16
ResNet
MobileNet
YOLOv5
YOLOv7
Convolutional Neural Network
CNN
Vision transformer
Neural networks (Computer science)
Accesso online:http://hdl.handle.net/10361/19296

Accesso online

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

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