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Dexiao Kong, Jiayi Wang, Qinghui Zhang, Junqiu Li and Jian Rong
Automated fruit-picking equipment has the potential to significantly enhance the efficiency of picking. Accurate detection and localization of fruits are particularly crucial in this regard. However, current methods rely on expensive tools such as depth ...
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Shengyong Xu, Yi Zhang, Wanjing Dong, Zhilong Bie, Chengli Peng and Yuan Huang
It is important to propose the correct decision for culling and replenishing seedlings in factory seedling nurseries to improve the quality of seedlings and save resources. To solve the problems of inefficiency and subjectivity of the existing traditiona...
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Rui Ren, Haixia Sun, Shujuan Zhang, Ning Wang, Xinyuan Lu, Jianping Jing, Mingming Xin and Tianyu Cui
To detect quickly and accurately ?Yuluxiang? pear fruits in non-structural environments, a lightweight YOLO-GEW detection model is proposed to address issues such as similar fruit color to leaves, fruit bagging, and complex environments. This model impro...
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Efrem Yohannes Obsie, Hongchun Qu, Yong-Jiang Zhang, Seanna Annis and Francis Drummond
Early detection and accurately rating the level of plant diseases plays an important role in protecting crop quality and yield. The traditional method of mummy berry disease (causal agent: Monilinia vaccinii-corymbosi) identification is mainly based on f...
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Guangyu Hou, Haihua Chen, Mingkun Jiang and Runxin Niu
Intelligent agriculture imposes higher requirements on the recognition and localization of fruit and vegetable picking robots. Due to its unique visual information and relatively low hardware cost, machine vision is widely applied in the recognition and ...
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