1. 简介

    陈明，博士，教授，广西师范大学计算机科学与工程学院博士生导师，广西高校海外百人计划 入选者。2001年与2004年分别获得华中科大机电学士与硕士学位，2009年获香港科大博士学位，方向为计算机辅助设计与计算机图形学。历任中兴通讯软件工程师，华为高级算法工程师，HKUST-WebEx研究院研发经理，香港JewelCAD/CAM项目的开发经理，哈工大深研院教师，香港富源欣科技CTO，现为广西师范大学计算机学院教师。先后主持国家自然基金3项、省部级项目3项，横向20余项；累计发表学术论文60余篇，知识产权40余项，注重产业应用与技术转化（近年主要专注机器视觉在工业领域落地应用）。欢迎具有激情、肯干的研究生报考。

研究兴趣：计算机辅助设计/计算机图形学/机器视觉

联络地址：Email:hustcm@sina.com

讲授课程： 软件工程/计算机图形学/系统分析与设计/Windows程序设计

我在寻找 “有追求/有激情/悟性高/态度端正/主动性强”的硕士生与博士生，如果有C++/C基础或各类大赛获奖证书更佳。

2. 代表项目

1.比快更快：大规模点云几何特征高性能识别与拟合研究, 国家自然基金， #62062015 2021.01-2024.12 

2.基于射线段取样的复杂网格模型大规模布尔运算的研究, 国家自然基金， #61662006 2017.01-2020.12 

3.基于高斯映射的可展曲面研究，国家自然基金，#61100088， 2012.01-2014.12

3. 代表论文

[1]Huang, Shuai, Ming Chen*, ShengLian Lu, ShouXin Chen and YongJian Zha. A Novel Algorithm: Fitting a Spatial Arc to Noisy Point Clouds with High Accuracy and Reproducibility. Measurement Science and Technology,38(6),(2021):1-16.

[2]Chen., Ming and Kai Tang*. G 2 Quasi-Developable Bezier Surface Interpolation of Two Space Curves. Computer-Aided Design 45, no. 11 (2013): 1365-1377.

[3]Ming, Chen*. and Tang. Kai. Quasi-Developable Surface Modeling of Contours with Curved Triangular Patches. Computers & Graphics 37, no. 7 (2013): 851-861.

[4]Chen, Ming and Kai* Tang. A Fully Geometric Approach for Developable Cloth Deformation Simulation. The Visual Computer 26, no. 6 (2010): 853-863.

[5]Tang, Kai* and Ming Chen. Quasi-Developable Mesh Surface Interpolation Via Mesh Deformation. IEEE Transaction on Visualization and Computer Graphics 15, no. 3 (2009): 518-528.

4. 代表产业应用

[1]领导团队研发高精度机器视觉检测系统应用到规模企业，包括欣旺达、宝马、伯恩、蓝思、小米、VIVO，华为等公司产线检测；检测精度和性能达到行业先进水平。

[2]领导团队研发3D 曲面与网格编辑引擎，国际著名三维珠宝CAD软件JewelCAD Pro基于该引擎开发。

[3]个人研发成果应用到全球领先的视频会议系统 WebEx系统，作为轻量级移动协同设计软件，支持异构CAD/CAE系统, 在福特汽车和波音应用。

5. 近期学术论文

[20]W.J Bi, M. Chen*, D.L Wu, S.L Lu, EBStereo: edge-based loss function for realtime stereo matching, [J]The Visual Computer, (2023)

[19]X Zhang, M Chen*, ZQ,Zhang, SL Lu. A Texture Detail-Oriented Generative Adversarial Network:Motion Deblurring for Multi-Textured Images. [J]Applied Intelligence, 53, 3255–3272 (2023)

[18]H.N Huang,M.Chen*,Z.Q Zhang,S.L Lu,An Efficient Feature Point Extraction Algorithm for Noisy Point Clouds,[J]Comput. Aided Des & App.,20(5), 936-945 (2023)

[17]J.N Hu,G. Li, H.L Mo, Y.B LV, T.T Qian, M. Chen, S.L Lu*, Crop Node Detection and Internode Length Estimation Using an Improved YOLOv5 Model,[J] Agriculture,13(2), 473 (2023)

[16]SX Chen , M Chen*, SL Lu. A Real Time Visual BooleanOperation on Triangular Mesh Models. [J]Comput.-Aided Des. and Appl.19. 470-480 (2022)

[15]YB Lai, SL Lu*,TT Qian, M Chen, S Zhen and G Li. Segmentation of Plant PointCloud based on Deep Learning Method. [J]Comput.-Aided Des. and Appl, 19(6) ,1117-1129 (2022) 

[14]Wenkang Chen，Shenglian Lu, Binghao Liu，Ming Chen，Guo Li，TingtingQian. CitrusYOLO: A Algorithm for Citrus Detection under Orchard EnvironmentBased on YOLOv4. [J]Multimedia Tools and Applications, 81, 31363–31389 (2022)

[13]B. Liu, M. Chen*, X. Zhang, N. Huang and S. Lu, A novel algorithm of detecting corner points for the contours of lines and arcs, MEMAT 2022; 2nd International Conference on Mechanical Engineering, Intelligent Manufacturing and Automation Technology,  1-4 (2022)

[12]X. Zhang, M. Chen and D. Wu, Industrial Character Image Motion Deblurring and Target Region Dynamic Location Method, IEEE  Pattern Recognition and Artificial Intelligence (PRAI), 658-663 (2022)

[11]Huang, Nanhua , Chen, Ming , Zhang, Zhengqin , Lu, Shenglian.An Efficient Feature Point Extraction Algorithm for Noisy Point Cloud, Proceedings of CAD’22, Beijing, China, July11-13, 2022, 267-270 ( (2022)

[10]Liu, Xiaoyu, Li, Guo, Chen, Wenkang , Liu, Binghao, Chen, Ming, Lu, Shenglian. Detection of Dense Citrus Fruits by Combining Coordinated Attention and Cross-Scale Connection with Weighted Feature Fusion. [J]Applied Sciences. 12. 6600 (2022)

[9] Lu, S. ,  Song, Z. , Chen, W. ,  Qian, T. ,  Zhang, Y. , &  Chen, M. Counting dense leaves under naturalenvironments via an improved deep-learning-based object detection algorithm,[J] Agriculture, 11(10), 1003(2021)

[8]Shuai Huang, Ming Chen*, ShengLian Lu,ShouXin Chen and YongJian Zha. A Novel Algorithm: Fitting a Spatial Arc toNoisy Point Clouds with High Accuracy and Reproducibility, [J]Measurement Science and Technology, 32. 10,1088 (2021) (16pp)

[7] Shenglian Lu, Guo Li, Ming Chen*. Methods and Tools for Modeling 3d Plants with Detailed Features. [J]Computer-Aided Design & Applications 15(5), 1034-1048(2021)

[6] Chen S , Chen M ,  Lu S . A Real TimeVisual Boolean Operation on 3D Models in Product Design Phase//  CAD Conference, 16-20. 10.14733/cadconfP.2021.( 2021)

[5]Shuai Huang., Ming Chen, Shenlian. Lu, Shouxin Chen and Yongjian Zha. Fitting the Space Line of High Repeatability to Noisy Point Cloud Data, Journal of Physics: Conference Series. 1820. 012193. 10.1088/1742-6596/1820/1/012193(2021).

[4] Lai., ibin, Shenglian Lu*., TingtingQian., Ming Chen. Zhen Song. and Guo Li. Segmentation of Plant-Part from 3dPoint Cloud Using Deep Learning and Multi-View Vision. // [C] CAD Conference, 218-222.Barcelona, Spain, 2021.

[3]Zha., YongJian, Ming Chen*. and ShengLianLu. Research on Point Cloud Registration of Industrial Parts Based on FGR-ICPAlgorithm.//[C] ICAMLDS 2021, 2021.

[2] 赖亦斌., 陆声链., 钱婷婷., 宋真. and 陈明. 植物三维点云分割方法研究. 应用科学学报,  2021

[1] 吴慧莹., 陈明(*)., 范晏君. and 黄帅. 复杂背景下的点阵字符识别研究. 计算机应用与软件,  2021

6. 知识产权

[10]陈明， 肖远辉, 一种用于高精度工件的空间平面数据拟合方法，CN114677400A，发明专利 2022

[9]陈明, 黄帅, 一种用于高精度工件的圆弧数据拟合方法，CN111243008B，发明专利 2022

[8]陈明，张正钦,一种针织鞋面布料的轮廓检测方法，CN115187624A，发明专利 2022

[7]陈明，闭韦杰 ,一种基于双边网格学习和边缘损失的双目立体匹配方法，CN115170921A，发明专利 2022

[6]陈明，李祺峰,一种用于带钢缺陷分类的多阶段半监督深度学习方法，CN114782777A，发明专利 2022

[5]陈明；张潇；刘博远；黄南华; 一种工业包装字符的去运动模糊方法, CN202110543088.1, 发明专利 2021. 

[4]陈明；黄南华；刘博远；张潇；一种特征点密度的点云特征提取方法CN113963014A，发明专利  2021. 

[3]车牌目标检测软件V1.0, #2020SR0855708，软著 

[2光线跟踪分层点云采样软件, #2020SR1026954，软著 

[1]字符检测与识别系统, #2020SR1027994，软著