Introducing AI in garment fault detection using YOLOv5 to reduce bottleneck
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.
Príomhchruthaitheoirí: | Sanjana, Jasia, Al Muhit, Abdullah, Zia, Asma |
---|---|
Rannpháirtithe: | Rhaman, Dr. Md. Khalilur |
Formáid: | Tráchtas |
Teanga: | English |
Foilsithe / Cruthaithe: |
Brac University
2024
|
Ábhair: | |
Rochtain ar líne: | http://hdl.handle.net/10361/22061 |
Míreanna comhchosúla
-
Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch
de réir: Uddin, Md. Minhaz, et al.
Foilsithe / Cruthaithe: (2023) -
Advancing autonomous navigation: YOLO-based road obstacle detection and segmentation for Bangladeshi environments
de réir: Mahmud, Ishtiaque, et al.
Foilsithe / Cruthaithe: (2024) -
Fire and disaster detection with multimodal quadcopter By machine learning
de réir: Afrin, Anika, et al.
Foilsithe / Cruthaithe: (2023) -
Occluded object detection for autonomous vehicles employing YOLOv5, YOLOX and Faster R-CNN
de réir: Mostafa, Tanzim, et al.
Foilsithe / Cruthaithe: (2022) -
Leveraging robust CNN architectures for real-time object recognition from conveyor belt
de réir: Moon, Nowrin Tasnim, et al.
Foilsithe / Cruthaithe: (2023)