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A platform for research: civil engineering, architecture and urbanism
Detection of Pine-Wilt-Disease-Affected Trees Based on Improved YOLO v7
Pine wilt disease (PWD) poses a significant threat to global pine resources because of its rapid spread and management challenges. This study uses high-resolution helicopter imagery and the deep learning model You Only Look Once version 7 (YOLO v7) to detect symptomatic trees in forests. Attention mechanism technology from artificial intelligence is integrated into the model to enhance accuracy. Comparative analysis indicates that the YOLO v7-SE model exhibited the best performance, with a precision rate of 0.9281, a recall rate of 0.8958, and an F1 score of 0.9117. This study demonstrates efficient and precise automatic detection of symptomatic trees in forest areas, providing reliable support for prevention and control efforts, and emphasizes the importance of attention mechanisms in improving detection performance.
Detection of Pine-Wilt-Disease-Affected Trees Based on Improved YOLO v7
Pine wilt disease (PWD) poses a significant threat to global pine resources because of its rapid spread and management challenges. This study uses high-resolution helicopter imagery and the deep learning model You Only Look Once version 7 (YOLO v7) to detect symptomatic trees in forests. Attention mechanism technology from artificial intelligence is integrated into the model to enhance accuracy. Comparative analysis indicates that the YOLO v7-SE model exhibited the best performance, with a precision rate of 0.9281, a recall rate of 0.8958, and an F1 score of 0.9117. This study demonstrates efficient and precise automatic detection of symptomatic trees in forest areas, providing reliable support for prevention and control efforts, and emphasizes the importance of attention mechanisms in improving detection performance.
Detection of Pine-Wilt-Disease-Affected Trees Based on Improved YOLO v7
Xianhao Zhu (author) / Ruirui Wang (author) / Wei Shi (author) / Xuan Liu (author) / Yanfang Ren (author) / Shicheng Xu (author) / Xiaoyan Wang (author)
2024
Article (Journal)
Electronic Resource
Unknown
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