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Min Hao, Quan Sun, Chuanzhong Xuan, Xiwen Zhang, Minghui Zhao and Shuo Song
To achieve automated farming management, including the recording, tracking, and statistics of sheep, we harness deep learning technology for sheep face recognition research, and the further development of lightweight sheep face recognition models. Deep l...
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Xingdong Sun, Yukai Zheng, Delin Wu and Yuhang Sui
The key technology of automated apple harvesting is detecting apples quickly and accurately. The traditional detection methods of apple detection are often slow and inaccurate in unstructured orchards. Therefore, this article proposes an improved YOLOv5s...
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Xinle Zhang, Jian Cui, Huanjun Liu, Yongqi Han, Hongfu Ai, Chang Dong, Jiaru Zhang and Yunxiang Chu
Soybean in the field has a wide range of intermixed weed species and a complex distribution status, and the weed identification rate of traditional methods is low. Therefore, a weed identification method is proposed based on the optimized Faster R-CNN al...
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Jian Song, Zhihong Yu, Guimei Qi, Qiang Su, Jingjing Xie and Wenhang Liu
There are many small objects in UAV images, and the object scale varies greatly. When the SSD algorithm detects them, the backbone network?s feature extraction capabilities are poor; it does not fully utilize the semantic information in the deeper featur...
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Bo Xu, Xiang Cui, Wei Ji, Hao Yuan and Juncheng Wang
Apple grading is an essential part of the apple marketing process to achieve high profits. In this paper, an improved YOLOv5 apple grading method is proposed to address the problems of low grading accuracy and slow grading speed in the apple grading proc...
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Yaodi Li, Jianxin Xue, Mingyue Zhang, Junyi Yin, Yang Liu, Xindan Qiao, Decong Zheng and Zezhen Li
The smart farm is currently a hot topic in the agricultural industry. Due to the complex field environment, the intelligent monitoring model applicable to this environment requires high hardware performance, and there are difficulties in realizing real-t...
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Tsu-Chuan Shen and Edward T.-H. Chu
Existing elevator systems lack the ability to display the number of people waiting on each floor and inside the elevator. This causes an inconvenience as users cannot tell if they should wait or seek alternatives, leading to unnecessary time wastage. In ...
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Yutan Wang, Zhenwei Xing, Liefei Ma, Aili Qu and Junrui Xue
The detection of Lingwu long jujubes in a natural environment is of great significance for robotic picking. Therefore, a lightweight network of target detection based on the SSD (single shot multi-box detector) is presented to meet the requirements of a ...
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Shuzhi Su, Runbin Chen, Xianjin Fang, Yanmin Zhu, Tian Zhang and Zengbao Xu
This study proposes a novel lightweight grape detection method. First, the backbone network of our method is Uniformer, which captures long-range dependencies and further improves the feature extraction capability. Then, a Bi-directional Path Aggregation...
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Huili Zhang, Xiaowen Zhou, Huan Li, Ge Zhu and Hongwei Li
This study is oriented towards machine autonomous mapping and the need to improve the efficiency of map point symbol recognition and configuration. Therefore, an intelligent recognition method for point symbols was developed using the You Only Look Once ...
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