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.

Podrobná bibliografie
Hlavní autoři: Moon, Nowrin Tasnim, Siddiqua, Sabiha Afrin, Parvin, Shahana, Muntaha, Sidratul, Hassan, K.M. Mehedi
Další autoři: Mostakim, Moin
Médium: Diplomová práce
Jazyk:English
Vydáno: Brac University 2023
Témata:
Neural network
Object detection
Conveyor belt
VGG16
ResNet
MobileNet
YOLOv5
YOLOv7
Convolutional Neural Network
CNN
Vision transformer
Neural networks (Computer science)
On-line přístup:http://hdl.handle.net/10361/19296

Internet

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

Podobné jednotky