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.

Detalles Bibliográficos
Autores principales: Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Otros Autores: Mostakim, Moin
Formato: Tesis
Lenguaje:English
Publicado: Brac University 2023
Materias:
Neural network
Object detection
Conveyor belt
VGG16
ResNet
MobileNet
YOLOv5
YOLOv7
Convolutional Neural Network
CNN
Vision transformer
Neural networks (Computer science)
Acceso en línea:http://hdl.handle.net/10361/19296

Internet

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

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