Accurate weed detection is essential for site-specific herbicide application in cotton production. However, variations in weed appearance, complex field backgrounds, uneven target distributions, and leaf occlusion can result in missed detections and false positives. To address these challenges, this study proposes YOLO...
Ling-Mei Wu, Li-Qiang Zhang, Rifeng Wang et al.· PLoS ONE· 0 citations
A time-frequency collaborative cross-device bearing fault diagnosis model based on supervised transfer learning with limited data that outperforms some current mainstream models in terms of both diagnostic accuracy and generalization performance, sufficiently demonstrating its effectiveness and practicality in cross-de...
The continuous growth of the global population has led to an increasing demand for food, yet the annual food losses caused by pests are immeasurable. Therefore, accurately identifying crop pests and adopting effective control strategies is of great practical significance. In recent years, intelligent crop pest classifi...