Yang Zidong

Prof. Yang Zidong


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 May 2025 in Preprints.org
Verified
Preprint
Open access
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YHYifan Hou
Yifan Hou
LYLijian Yao
Lijian Yao
YZYang Zidong
Yang Zidong
GLGaozhong Liu
Gaozhong Liu
RMRong Ma
Rong Ma
In order to achieve the recognition and detection of pear tree trunks in natural envi-ronment and solve the problem of low recognition rate caused by the complex recogni-tion environment, this study uses binocular camera to construct a visual localisation system for pear tree trunks, and proposes a pear tree trunk recognition and localisation model based on the improved YOLOv5s model. The model replaces C3 with C3TR module and embeds the CA attention mechanism, replaces the standard convolution in the Neck part with GSConv, and replaces it with the bidirectional feature pyramid network BiFPN structure; combined with the acquired depth information of the pear tree trunk, the 3D spatial coordinate information of the pear tree trunk is obtained by using the stereo imaging principle of the binocular camera. In order to verify the effec-tiveness of the proposed method, the effectiveness of YOLOv5s-pear is compared and analysed with the other three models, YOLOv4, YOLOv4-Tiny and YOLOv5s, in terms of the detection results, and the experimental results show that the accuracy of YOLOv5s-pear is improved compared with YOLOv5s, YOLOv4-Tiny and YOLOv4 by 2.1%, 6.2% and 7.7%; the positioning test shows that the error rate between the shoot-ing distance and the actual distance is 1.48%. The improved YOLOv5s model, YOLOv5s-pear, improves the model's performance in dealing with target detection in multi-scale and complex environments, and can realise the rapid identification and precise positioning of pear tree trunks, which can provide a reference for the research and development of autonomous navigation devices.

1 January 2016 in Science Innovation
Verified
Journal Article
Open access
PDF file
YZYang Zidong
Yang Zidong
NYNi Yihua
Ni Yihua
YLYao Lijian
Yao Lijian
NZNi Zhongjin
Ni Zhongjin
Based on innovative design education of agroforestry equipment,the 3D design, innovative design and modeling parts of agroforestry equipment run through entire teaching in this paper. By CNC machining centers and 3D printer as a platform, and fused the Maker education in whole education process. Thus the students not only have a virtual innovative design, but also can get real experience of manufacturing process and the products. Building the course teaching model based on Maker education. The innovative design capabilities is foundation of Maker education. Based on business demand for the rapidly capabilities of agroforestry equipment R&D and the law of creative education, the teaching process was broken down to three interconnected modules.The process teaching of theory, practice and agroforestry equipment innovation was designed integration. And the "theory - practice - innovation" teaching mode was also implemented. The task-driven project teaching has taken to implement each project. According to the requirements of Maker education, building a 3D printing service support system of education to enrich agroforestry equipment learning.It can provide practical reference for mechanical engineering education.