This research focuses on trading card quality inspection, where defects have a significant
effect on both the quality inspection and grading. The present inspection procedure is …

The accurate identification of tomato maturity and picking positions is essential for efficient
picking. Current deep-learning models face challenges such as large parameter sizes …

Accurately detecting surface defects is crucial for maintaining the quality of steel products.
The existing methods often struggle with identifying small defects in complex scenes. To …

Reaction-bonded silicon carbide (RB-SiC) is a typical brittle material. Surface removal
modes such as brittle fracture and ductile groove will directly influence the performance of …

The detection of small objects within multiscale defects amidst complex background
interference presents a formidable challenge in industrial defect detection. To address this …

To address the issues of varying defect scales and background interference on steel
surfaces, which result in low detection accuracy and slow speed in traditional YOLOv8 …

In recent years, the rapid development of deep learning technology has provided many
methods for defect detection in industrial application scenarios. However, defect detection in …

The silkworm is a crucial commercial insect, and the silk from its cocoon is a significant
material used to produce top-quality garments. In the breeding environment, silkworms are …

To address the issues of varying defect scales and background interference on steel
surfaces, which result in low detection accuracy and slow speed in traditional YOLOv8 …