Personal Profile:
Mei Shuang, male, born in October 1989, PhD in industrial vision, associate professor, master/doctoral supervisor, CUG Scholar – Young Talent, Outstanding Young Talent of Wuhan “Yellow Crane Talents Program”, is now the deputy head of the Department of Mechanical Engineering of the School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan). From 2012 to 2017, he studied for his PhD in the team of Academician Xiong Youlun at the State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, majoring in machine vision, precision measurement and inspection, and deep learning. He has published many SCI papers in the fields of semiconductor manufacturing, intelligent sensing, instrumentation and measurement technology, and his technical achievements have been applied and supported in many enterprises. He was awarded Outstanding Young Talent of Wuhan “Yellow Crane Talents Program”, the second prize of Shandong Machinery Industry Science and Technology Award, and the Second-class Award for Progress in Science and Technology of Hubei Province. He has presided over 1 project of the National Natural Science Foundation of China for the Youth, 2 GF projects, 6 enterprise-sponsored projects in semiconductor and industrial visual defect detection (“Development of MiniLED Wafer Appearance Defect Detection System”, “Development of Automatic Optical Inspection Intelligent Plug-in Library”, “Development of 3C Visual Appearance Defect Detection Algorithm”, etc.), participated in one major innovation project in Hubei Province as a core personnel (“Research and Development of TFT-LCD Optical Automatic Inspection Equipment”), and participated in 1 major instrument program of the NSFC, 2 general programs of the NSFC and 1 project of National Key R&D Program of China. He is also the reviewer of several internal journals, such as IEEE TIM, MST, and Neurocomputing.
University-Enterprise Collaboration and Base Construction:
He is a distinguished professor of Guangzhou Institute of Advanced Technology, the head of the “Industrial Visual Inspection Industrial Technology Innovation Center” and head of the “Industrial Visual Inspection and Measurement” Group of China University of Geosciences, the head of the Graduate Joint Training Base of China University of Geosciences and Dongguan Kobarry Automation Technology Co., Ltd and the head of the Graduate Joint Training Base of China University of Geosciences and Guangzhou GRG Metrology & Test Co., Ltd. Wuhan Branch. His team has been approved as a provincial-level teaching team and an excellent young and middle-aged scientific and technological innovation team in Hubei Province.
Contact Information:
Office location: Room 335, No. 2 Teaching Building, School of Mechanical Engineering and Electronic Information, China University of Geosciences (Wuhan)
Email: meishuang@cug.edu.cn
Admission Information:
Doctoral program: Control Science and Engineering (081100) (intelligent perception and pattern recognition, advanced manufacturing technology and equipment)
Master’s program: Mechanical Engineering (0802), Mechanics (0855), Information and Communication Engineering (0810), Electronic Information (0854)
★ 4-5 master degree candidates and 1 PhD candidate are admitted each year.
Main Experiences:
2018/08-present: Associate professor, School of Mechanical Engineering and Electronic Information, China University of Geosciences
2012/09-2017/12: PhD, School of Mechanical Science & Engineering, Huazhong University of Science and Technology
2008/09-2012/06: Bachelor, School of Mechanical Engineering and Electronic Information, China University of Geosciences
Main Research Fields:
1. Industrial vision inspection and precision measurement: Based on the theories related to machine vision and deep learning, carry out the research on visual measurement, localization, recognition and detection algorithms in special scenarios, and realize the application of digital image processing and analysis related methods in intelligent manufacturing industrial scenarios.
2. 3D visual reconstruction and robot visual servo: Based on the theories related to multi-view geometry and feature engineering in computer vision, carry out the research on multi-view multi-eye structured light and line laser 3D reconstruction methods, and the vision servo technology for calibrated and uncalibrated robots, to achieve high-precision 3D measurement and scene perception.
3. Digital Image Correlation (DIC) Theory and applications: Based on theories related to digital image processing, numerical computation and deep neural networks, carry out the research on new methods for real-time and efficient 2D and 3D digital scattering correlation, to realize displacement, deformation and morphology measurement of solid materials and structural surfaces.
Programs:
National Natural Science Foundation of China for the Youth, “Research on key technologies of product surface defect detection in industrial scene based on semantic segmentation depth model” (51905502), 2020/01-2022/12, PI
Program supported by the Fundamental Research Funds for the Central Universities, “Deep learning-based product surface defect detection technology and application research” (CUG180324), 2019/01-2021/12, PI
Wuhan Science and Technology Bureau, 2019 Wuhan Yellow Crane Talents Program (20230750068), 2020/01-2022/12, PI
GF Project, “XXXX fault and condition monitoring XXXX,” (20210710251), 2021/09-2022/05, PI
GF Project, “XXXX mechanism multifunctional test XXXX” (20210710268), 2021/12-2022/10, PI
Enterprise-sponsored project, “Development of 3C visual appearance defect detection algorithm” (2021076350), 2021/07-2022/01, PI
Enterprise-sponsored project, “AOI intelligent software plug-in library development project” (2022076446), 2022/06-2023/04, PI
Enterprise-sponsored project, “Development of the roof condition image detection system and algorithm for Multiple Units” (2022076860), 2022/06-2023/06, PI
Enterprise-sponsored project, “Development of Mini LED wafer appearance defect detection system” (2022076249), 2022/04-2022/11, PI
Enterprise-sponsored project, “Vision-based obstacle recognition, path planning, and compliance control development” (2022076211), 2022/04-2023/04, participant
Enterprise-sponsored project, “Research on the information modeling and intelligent diagnosis system of drainage pipeline”, general enterprise sponsored program (2020056717), 2020/10-2021/12, participant
Major program of technical innovation foundation of Hubei Province, “Research and development of TFT-LCD optical automatic detection equipment” (2016AAA009), concluded, participant
General Program of the National Natural Science Foundation of China, “Research on the long distance directional crossing guide hole formation mechanism of high-power fiber laser drilling” (41972325), under study, participant
Project of National Key R&D Program of China, “Key technology and equipment development of 5000m geological core drilling rig” (2020073128), concluded, participant
General Program of the National Natural Science Foundation of China, “Research and application of particle image velocity measurement and tracing mechanism in hypersonic flow field” (51475193), concluded, participant
Major instrument program of the National Natural Science Foundation of China, “Development and application of real-time accurate measurement system in hypersonic flow field” (51327801), concluded, participant
Selected Papers:
Shuang Mei, Jiangtao Cheng, Xin He, Hao Hu, Guojun Wen. A Novel Weakly Supervised Ensemble Learning Framework for Automated Pixel-Wise Industry Anomaly Detection. IEEE Sensors Journal. 2022, 22(2):1560-1570.
Shuang Mei, Qi Cai, Zhijun Gao, Hao Hu, Guojun Wen. Deep Learning Based Automated Inspection of Weak Microscratches in Optical Fiber Connector End-Face. IEEE Transactions on Instrumentation and Measurement, 2021, 70:3511710.
Hao Hu, Shuang Mei, Liming Fan, Huigang Wang. A Line-Scanning Chromatic Confocal Sensor for Three-Dimensional Profile Measurement on Highly Reflective Materials. Review of Scientific Instruments, 2021, 92(5):053707.
Qiu Wangde, Wen Guojun, Shuang Mei*, Liu Xingyue and He Xin. AR-DIC: A Novel Automatic Optical Strategy for Displacement Measurement of the Curved-In-Place Pipe under Dynamic Fracturing, IEEE Transactions on Instrumentation and Measurement, DOI: 10.1109/TIM.2023.3272395.
Hu Hao, Wei Bin, Shuang Mei, et al. A Two-Step Calibration Method for Vision Measurement With Large Field of View. IEEE Transactions on Instrumentation and Measurement, 2022,71:5006910.
Yong Lee, Shuang Mei*.Diffeomorphic Particle Image Velocimetry, IEEE Transactions on Instrumentation and Measurement, 2022, 71(1):1-10.
Ma Yiming, Wen Guojun, Cheng siyi, He Xin, Shuang Mei*. Multimodal convolutional neural network model with information fusion for intelligent fault diagnosis in rotating machinery, Measurement Science and Technology, 2022, 33(12): 125109.
Zhao Yahong, Yan Xuefeng, Deng Caiying, Liu Han, Shuang Mei, Mechanical Performance Study of Pipe-Liner Composite Structure Based on the Digital Image Correlation Method. IEEE Transactions on Instrumentation and Measurement, 2023:3504212.
Guojun Wen, Zhijun Gao, Qi Cai, Yudan Wang, Shuang Mei*. A Novel Method Based on Deep Convolutional Neural Networks for Wafer Semiconductor Surface Defect Inspection, IEEE Transactions on Instrumentation and Measurement, 2020, 69(12): 9668-9680.
Shuang Mei, Hua Yang*, Zhouping Yin. An Unsupervised-Learning-Based Approach for Automated Defect Inspection on Textured Surfaces. IEEE Transactions on Instrumentation and Measurement, 2018, 67(6) :1266-1277.
Shuang Mei, Yudan Wang, Guojun Wen. Automatic Fabric Defect Detection with A Multi-Scale Convolutional Denoising Autoencoder Network Model. Sensors, 2018, 18(4): 1-18.
Shuang Mei, Yudan Wang, Guojun Wen. Automated Inspection of Defects in Optical Fiber Connector End Face Using Novel Morphology Approaches. Sensors, 2018, 18(5): 1-17.
Shuang Mei, Hua Yang, Zhouping Yin. Unsupervised-Learning-Based Feature-Level Fusion Method for Mura Defect Recognition. IEEE Transactions on Semiconductor Manufacturing, 2017, 30 (1) :105-113.
Hua Yang, Shuang Mei, Kaiyou Song, Bo Tao, Zhouping Yin. Transfer Learning Based Online Mura Defect Classification. IEEE Transactions on Semiconductor Manufacturing, 2017, 31 (1) :116-123.
Shuang Mei, Hua Yang, Zhouping Yin. Discriminative Feature Representation for Image Classification via Multi-Modal Multi-Task Deep Neural Networks, Journal of Electronic Image, 2017, 26 (1) :013023.
Hua Yang, Kaiyou Song, Shuang Mei, Zhouping Yin. An Accurate Mura Defect Vision Inspection Method Using Outlier-Prejudging-Based Image Background Construction and Region-Gradient-Based Level Set. IEEE Transaction on Automation Science and Engineering, 2018, 15(4) :1704-1721.
Other Achievements:
Second Prize for Progress in Science and Technology of Hubei Province, Shuang Mei (5/15), “Research on key technologies for the whole life cycle of large non-development horizontal directional drilling rigs”, Hubei Provincial People’s Government, 2019
Second Prize of Machinery Industry Science and Technology Award of Shandong Province, Shuang Mei (3/5), “A distribution calibration method for large field-of-view vision measurement system”, 2022
Outstanding Young Talent of Wuhan “Yellow Crane Talents Program”, Shuang Mei, Wuhan Municipal People’s Government, 2019
Granted Invention Patent. Shuang Mei, Xiaotan Men, Guojun Wen, Jiangtao Cheng. Optical fiber endface defect detection method, equipment and storage media, 2021/10/19, China, CN112950561B
Granted Invention Patent. Shuang Mei, Guojun Wen, Zhijun Gao, Qi Cai. Vision-guided robot grasping, classification system and method for multi-source data fusion, 2020/11/20, China, CN112288819B
Granted Invention Patent. Lei Li, Shuang Mei, Guojun Wen, Weijie Ma. A four-line, four-eye 3D laser scanner and scanning method, 2021/04/12, China, CN113310430B
Granted Invention Patent. Weijie Ma, Shuang Mei, Guojun Wen, Lei Li. A multi-camera reconstruction method based on DLP surface structured light, 2021/02/03, China, CN113012277B
Granted Invention Patent. Hua Yang, Zhouping Yin, Youlun Xiong, Shuang Mei, Qianglong Zhong, Buyang Zhang, Yong Li. A flow field real-time accurate measurement system and method, 2014/04/02, China, 201310693222.1
Granted Invention Patent. Hua Yang, Zhouping Yin, Jin Lu, Shuang Mei, Lianzheng Chen. An image acquisition device for TFT-LCD defect automatic inspection line, 2016/08/31, China, 201410755429.1
