[1] |
Liu Yuping, Liu Chengfei, Zhao Pingwei.
Detection method of rice leaf disease based on DeepLabv3—Faster R—CNN
[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(4): 108-113.
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[2] |
Ding Zhanbo, Xu Jian, Zhu Yaolin, Zhang Yongjin, Liu Chenyu.
Research on prickly ash cluster detection based on lightweight YOLO model
[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(4): 120-125.
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[3] |
Xu Yuchao, , Wu Qian, , Zhang Bingyuan, , , Zhou Lingli, , Ren Ni, , , Zhang Meina, , .
Review on lightweight deep learning networks for object detection in crops
[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(3): 261-270.
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[4] |
Luo Liuming, Li Yanzhou, Shi Meiqi, Huang Xin, Chen Xi.
A identification method for sugarcane weed based on YOLOv8n
[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(2): 237-244.
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[5] |
Xia Zilin, Zhang Xinzhou, Wang Wenbo, Xia Xianfei, Chen Lan, Gu Jinan.
Research on high precision detection method of broad bean pods based on machine vision
[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(1): 157-163.
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[6] |
Peng Yong, Qiao Yinhu, Zhang Chunyan, Yao Jie, Bao Dianling.
Research of strawberry detection method with improved YOLOv5 model
[J]. Journal of Chinese Agricultural Mechanization, 2025, 46(1): 213-219.
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[7] |
Zhang Chuandong, Qi Lu, Ding Huali.
Detection method of multi variety grape cluster based on improved YOLOv8n deep learning algorithm
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(9): 220-226.
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[8] |
Zhao Xiaoxia, Cheng Man, Yuan Hongbo.
A multi‑object tracking method for sheep based on StrongSORT algorithm
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(8): 180-188.
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[9] |
LiuXing, Gu Jinan, Huang Zedong, Zhang Wenhao, Zhang Wei.
Research on apple point cloud semantic segmentation based on deep learning
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(8): 223-227.
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[10] |
Zhou Sijie, Liu Tianqi, Chen Tianhua.
Research on rice disease recognition based on improved YOLOv5 algorithm
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(8): 246-253.
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[11] |
Yue Yaohua, , , Zhang Wei, , , Qi Liqiang, , .
Research on the identification method of soybean flower growth status in the field based on improved YOLOv5
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(7): 188-193.
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[12] |
Zhang Yanjun, , Zhao Jianxin, .
Research on daylily joint detection algorithm based on multiple neural networks
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(7): 228-234.
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[13] |
Huang Yao, He Jing, Fu Rao, Liu Gang, , Lin Yuanyang.
Application analysis of the YOLOv5s-CBAM algorithm for the identification of eggs of Pomacea
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(6): 223-228.
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[14] |
Luo Xin, Li Jiaqiang, He Chao.
A visual monitoring method for Macadamia nuts based on improved YOLOv4
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(5): 217-222.
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[15] |
Huang Wei, Liu Yiting, , Li Peijuan, Chen Guangming, .
Detection method of apple ripeness based on improved YOLOXS
[J]. Journal of Chinese Agricultural Mechanization, 2024, 45(3): 226-232.
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