1. Automated Defect Detection for Mass-Produced Electronic Components Based on YOLO Object Detection Models
- Author
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Mao, Wei-Lung, Wang, Chun-Chi, Chou, Po-Heng, and Liu, Yen-Ting
- Abstract
Since the defect detection of conventional industry components is time-consuming and labor-intensive, it leads to a significant burden on quality inspection personnel and difficult to manage product quality. In this article, we propose an automated defect detection system for the dual in-line package (DIP) that is widely used in industry, using digital camera optics and deep learning (DL)-based model. The two most common defect categories of DIP are examined:
$\text {1)}$ $\text {2)}$ - Published
- 2024
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