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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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Shuhe Zheng, Yang Liu, Wuxiong Weng, Xuexin Jia, Shilong Yu and Zuoxun Wu
Recognition and localization of fruits are key components to achieve automated fruit picking. However, current neural-network-based fruit recognition algorithms have disadvantages such as high complexity. Traditional stereo matching algorithms also have ...
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Victoria Kamenchuk, Boris Rumiantsev, Sofya Dzhatdoeva, Elchin Sadykhov and Azret Kochkarov
Urban vertical farming is an innovative solution to address the increasing demand for food in densely populated cities. With advanced technology and precise monitoring, closed urban vertical farms can optimize growing conditions for plants, resulting in ...
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Sheng Jiang, Ziyi Liu, Jiajun Hua, Zhenyu Zhang, Shuai Zhao, Fangnan Xie, Jiangbo Ao, Yechen Wei, Jingye Lu, Zhen Li and Shilei Lyu
Fruit maturity is a crucial index for determining the optimal harvesting period of open-field loofah. Given the plant?s continuous flowering and fruiting patterns, fruits often reach maturity at different times, making precise maturity detection essentia...
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Junchi Zhou, Wenwu Hu, Airu Zou, Shike Zhai, Tianyu Liu, Wenhan Yang and Ping Jiang
Considering the high requirements of current kiwifruit picking recognition systems for mobile devices, including the small number of available features for image targets and small-scale aggregation, an enhanced YOLOX-S target detection algorithm for kiwi...
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