Apple-YOLO: A novel mobile terminal detector based on YOLOv5 for early apple leaf diseases
Jinjiang Li¹, Xianyu Zhu¹, Runchang Jia¹, Bin Liu¹, Cong Yu¹
¹College of Information Engineering, Northwest A&F University, Yangling, China
Published in In the proceedings of 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), 2022
Keywords: YOLOv5, mobile detection, apple leaf diseases, early detection
Abstract
This paper presents Apple-YOLO, a novel mobile terminal detector based on YOLOv5 for early detection of apple leaf diseases. The proposed method improves upon the original YOLOv5 architecture by incorporating mobile-specific optimizations and early disease detection capabilities. Experimental results demonstrate that Apple-YOLO achieves superior performance in terms of accuracy and speed compared to existing mobile detection methods for agricultural applications.
Recommended citation: Jinjiang Li, Xianyu Zhu, Runchang Jia, Bin Liu, Cong Yu, "Apple-YOLO: A novel mobile terminal detector based on YOLOv5 for early apple leaf diseases." In the proceedings of 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC), 2022.
@inproceedings{li2022apple,
title={Apple-YOLO: A novel mobile terminal detector based on YOLOv5 for early apple leaf diseases},
author={Li, Jinjiang and Zhu, Xianyu and Jia, Runchang and Liu, Bin and Yu, Cong},
booktitle={In the proceedings of 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)},
year={2022},
publisher={IEEE}
}