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.

Opis bibliograficzny
Główni autorzy:	Uddin, Md. Minhaz, Foysal, Sadi Mahmud, Rahman, Sadia, Risti, Nushara Tazrin, Sarmin, Sanzeda Akter
Kolejni autorzy:	Rhaman, Dr. Md. Khalilur
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2023
Hasła przedmiotowe:	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.
Dostęp online:	http://hdl.handle.net/10361/19356

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