COMPUTER VISION BASED INDUSTRIAL INSPECTION SYSTEM
| dc.contributor.author | Adel BELLAHCENE | |
| dc.date.accessioned | 2025-01-21T20:03:41Z | |
| dc.date.available | 2025-01-21T20:03:41Z | |
| dc.date.issued | 2025-01-21 | |
| dc.description.abstract | This review explores the cutting-edge applications of computer vision (CV) in industrial inspection. We highlight the limitations of traditional methods and showcase how CV, coupled with Machine Learning (ML) and Deep Learning (DL) techniques like Convolutional Neural Networks (CNNs), is revolutionizing defect detection and quality control. The review explores the recent advancements in real-time object detection with YOLO models, emphasizing their potential for high-speed production lines. We conclude by discussing the future of CV in industrial inspection, including integration with robotics and sensor fusion for intelligent and comprehensive inspection systems | |
| dc.identifier.uri | https://dspace.estin.dz/handle/123456789/22 | |
| dc.language.iso | en | |
| dc.publisher | Tassadit | |
| dc.title | COMPUTER VISION BASED INDUSTRIAL INSPECTION SYSTEM | |
| dc.type | Thesis |
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