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Bin Li, Huazhong Lu, Xinyu Wei, Shixuan Guan, Zhenyu Zhang, Xingxing Zhou and Yizhi Luo
Accurate litchi identification is of great significance for orchard yield estimations. Litchi in natural scenes have large differences in scale and are occluded by leaves, reducing the accuracy of litchi detection models. Adopting traditional horizontal ...
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Yaoqiang Pan, Xvlin Xiao, Kewei Hu, Hanwen Kang, Yangwen Jin, Yan Chen and Xiangjun Zou
In an unmanned orchard, various tasks such as seeding, irrigation, health monitoring, and harvesting of crops are carried out by unmanned vehicles. These vehicles need to be able to distinguish which objects are fruit trees and which are not, rather than...
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Li Sun, Jingfa Yao, Hongbo Cao, Haijiang Chen and Guifa Teng
In agricultural production, rapid and accurate detection of peach blossom bloom plays a crucial role in yield prediction, and is the foundation for automatic thinning. The currently available manual operation-based detection and counting methods are extr...
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Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ...
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Junsheng Liu, Guangze Zhao, Shuangxi Liu, Yi Liu, Huawei Yang, Jingwei Sun, Yinfa Yan, Guoqiang Fan, Jinxing Wang and Hongjian Zhang
In the realm of automated apple picking operations, the real-time monitoring of apple maturity and diameter characteristics is of paramount importance. Given the constraints associated with feature detection of apples in automated harvesting, this study ...
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