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What is Applsci 13 10063 about?

This study proposes an improved tomato disease and pest detection model called YOLOv5n-VCW based on the YOLOv5n object detection framework. The improvements include using an Efficient Vision Transformer for feature extraction, a Content-Aware ReAssembly of FEatures algorithm for upsampling, and a Wise-IoU loss function. Experimental results show the improved model achieves higher accuracy (2.3% higher mAP50 and 1.7% higher mAP50:95) than YOLOv5n while reducing model parameters by 0.4M and computational comp

Author

Ahmed Amamou

Language

EN