Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch

Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Xehetasun bibliografikoak
Egile Nagusiak: Uddin, Md. Minhaz, Foysal, Sadi Mahmud, Rahman, Sadia, Risti, Nushara Tazrin, Sarmin, Sanzeda Akter
Beste egile batzuk: Rhaman, Dr. Md. Khalilur
Formatua: Thesis
Hizkuntza:English
Argitaratua: Brac University 2023
Gaiak:
TILDA
YOLOv7
YOLOv7x
YOLOv7-W6 CNN
RCNN
DCNN
Faster-RCNN
Neural Networks
Real-Time
Computer vision
Fault
Defect
Detection
Garments
Hole
Stitch
Seam
Roboflow
Signal detection.
Sarrera elektronikoa:http://hdl.handle.net/10361/19356

Internet

http://hdl.handle.net/10361/19356

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