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Yi Yang, Guankang Zhang, Shutao Ma, Zaihua Wang, Houcheng Liu and Song Gu
The accurate detection and counting of flowers ensure the grading quality of the ornamental plants. In automated potted flower grading scenarios, low detection precision, occlusions and overlaps impact counting accuracy. This study proposed a counting me...
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Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
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Bao She, Jiating Hu, Linsheng Huang, Mengqi Zhu and Qishuo Yin
To grasp the spatial distribution of soybean planting areas in time is the prerequisite for the work of growth monitoring, crop damage assessment and yield estimation. The research on remote sensing identification of soybean conducted in China mainly foc...
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Liusheng Han, Xiangyu Wang, Dan Li, Wenjie Yu, Zhaohui Feng, Xingqiang Lu, Shengshuai Wang, Zhiyi Zhang, Xin Gao and Junfu Fan
The lack of high-spectral and high-resolution remote sensing data is impeding the differentiation of various fruit tree species that share comparable spectral and spatial features, especially for evergreen broadleaf trees in tropical and subtropical area...
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Xiang Sun, Yisheng Miao, Xiaoyan Wu, Yuansheng Wang, Qingxue Li, Huaji Zhu and Huarui Wu
To enhance the transplantation effectiveness of vegetables and promptly formulate subsequent work strategies, it is imperative to study the recognition approach for transplanted seedlings. In the natural and complex environment, factors like background a...
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