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Jun Tie, Weibo Wu, Lu Zheng, Lifeng Wu and Ting Chen
When aiming at the problems such as missed detection or misdetection of recognizing green walnuts in the natural environment directly by using target detection algorithms, a method is proposed based on improved UNet3+ for green walnut image segmentation,...
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Zhengyang Zhong, Lijun Yun, Feiyan Cheng, Zaiqing Chen and Chunjie Zhang
This paper proposes a lightweight and efficient mango detection model named Light-YOLO based on the Darknet53 structure, aiming to rapidly and accurately detect mango fruits in natural environments, effectively mitigating instances of false or missed det...
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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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Hailiang Gong, Xi Wang and Weidong Zhuang
This study focuses on real-time detection of maize crop rows using deep learning technology to meet the needs of autonomous navigation for weed removal during the maize seedling stage. Crop row recognition is affected by natural factors such as soil expo...
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Fei Huang, Yanming Li, Zixiang Liu, Liang Gong and Chengliang Liu
The leaf area of pak choi is a critical indicator of growth rate, nutrient absorption, and photosynthetic efficiency, and it is required to be precisely measured for an optimal agricultural output. Traditional methods often fail to deliver the necessary ...
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