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YOLOv8 for Real-Time Insect Detection by Sukanya Varpe is a document available to read on EtoBox.
This paper presents a generalized deep learning approach using YOLOv8 for real-time insect detection in precision agriculture, aiming to enhance pest control by detecting any insect type across various crops. The authors conducted extensive testing, achieving a mean average precision (mAP) of 0.967 for the model, demonstrating its effectiveness compared to previous narrow-focused solutions. The study emphasizes the need for a comprehensive dataset to fully leverage YOLOv8
- Author
- Sukanya Varpe
- Language
- EN