According to the demands of enterprises, in the current field of chip screening, there are significant loopholes in the traditional manual screening method. It not only takes a lot of time and effort but also leads to a high rate of false detection, which increases the labor cost for enterprises. The traditional chip defect detection work usually adopts the manual visual inspection method. When defective chips are found, these unqualified products are manually removed. However, manual visual inspection has many variable factors and suffers from a series of problems such as low recognition accuracy, poor real-time performance, and high false detection rate. With the gradual increase in chip production speed and the ever-increasing quality requirements for chips, the traditional manual visual inspection method can no longer meet the industrial requirements for real-time chip detection. This system has optimized the detection performance of YOLOv8, enabling it to accurately identify chip defects in complex backgrounds and possess real-time detection capabilities. It is applicable to multiple fields such as industrial inspection. Experimental results show that the system achieves high precision and mAP [2]on the test set, effectively replacing traditional manual inspection methods and significantly enhancing detection efficiency and accuracy.
