Machine Vision and Intelligent Perception (Industrial Intelligent Inspection)

Image Processing and Pattern Recognition (Deep Learning)

Robotics intelligent equipment (Precision measurement, assembly, control)

2013-09 - 2016-06     PhD, Institute of Automation, Chinese Academy of Sciences

2018.10 - Present       Associate Professor, Institute of Automation, Chinese Academy of Sciences

2018.12 to 2019.12    Visiting Scholar, FEIT, University of Technology Sydney, Australia (Co-Supervisor: Prof. Chin-Teng Lin, IEEE Fellow)

2016.07 to 2018.09    Assistant Professor, Institute of Automation, Chinese Academy of Sciences

google scholar

[1]  Tao Xian , Qu Zhen , Luo Hengliang , Han Jianwen ,He Yonghao , Liu Danfeng , Lv Chengkan ,  Shen Fei , Zhang Zhengtao, The Second-place Solution for CVPR VISION 23 Challenge Track 1 - Data Effificient Defect Detection. arXiv preprint arXiv:2306.14116 ​

[2]  Tao X*，Adak C., Chun Pang-jo, Yan SH, Liu HP. ViTALnet:Anomaly Localization on Industrial Textured Surfaces with Hybrid Transformer[J]. IEEE Transactions on Instrumentation and Measurement, 2023.

[3]   Tao X*,  Zhang DP, Ma W, Hou Z, Lu Z, Adak C. "Unsupervised Anomaly Detection for Surface Defects with 

Dual-Siamese Network." IEEE Transactions on Industrial Informatics, 2022. (SCI, Top 1%，IF: 11.648)

[4]   Tao X*，Gong XY, Zhang X, Yan SH, Adak C. Deep Learning for Unsupervised Anomaly Localization in Industrial Images: A Survey[J]. IEEE Transactions on Instrumentation and Measurement, 2022.

[5]  Tao X*,Yan SH, Gong XY,Adak C. Learning Multi-Resolution Features for Unsupervised Anomaly Localization on Industrial Textured Surfaces, IEEE Transactions on Artificial Intelligence, 2022. 

[6]   Yan SH, Xu D,Tao X. Hierarchical Policy Learning with Demonstration Learning for Robotic Multiple Peg-in-Hole Assembly Tasks[J]. IEEE Transactions on Industrial Informatics, 2023. (SCI, Top 1%，IF: 11.648)

[7]   Yan SH, Tao X, Xu D. Image-based Visual Servoing System for Components Alignment Using Point and Line Features[J]. IEEE Transactions on Instrumentation and Measurement, 2022.

[8]   Tao X*, Ma W, Lu Z, Hou Z. Conductive Particle Detection for Chip on Glass Using Convolutional Neural

 Network[J]. IEEE Transactions on Instrumentation and Measurement, 2021. （SCI, Top15%）

[9]  Tao X*, Zhang D, Wang Z, Liu X, Zhang H, Xu D. Detection of power line insulator defects using aerial images analyzed with convolutional neural networks[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2020, 50(4): 1486-1498. SCI,  Google Scholar：160, web of science : 79, Top 1%，IF: 13.451, ESI Highly Cited Paper ）

[10]  Tao X*, Zhang D, Hou W, Ma W, Xu D. Industrial Weak Scratches Inspection Based on Multifeature Fusion Network[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 70: 1-14. （SCI, Top15%）

[11]  Tao X, Wang Z, Zhang ZT*, et al. Wire defect recognition of spring-wire socket using multitask convolutional neural networks[J]. IEEE Transactions on Components, Packaging and Manufacturing Technology, 2018, 8(4): 689-698. （SCI）

[12]  Tao X, Zhang Z, Zhang F, Xu D.*. A novel and effective surface flaw inspection instrument for large-aperture optical elements[J]. IEEE Transactions on Instrumentation and Measurement, 2015, 64(9): 2530-2540. （SCI, Top15%）

[13]   Hou W, Tao X*, Xu D. A Self-Supervised CNN for Particle Inspection on Optical Element[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-12. （SCI, Top15%）

[14]  Hou W, Tao X*, Xu D. Combining Prior Knowledge With CNN for Weak Scratch Inspection of Optical Components[J]. IEEE Transactions on Instrumentation and Measurement, 2020, 70: 1-11. （SCI, Top15%）

[15]   Yan SH, Tao X*, Xu D. High-precision robotic assembly system using three-dimensional vision[J]. International Journal of Advanced Robotic Systems. 2021. （SCI）

[16]   Tao Xian*, Hou Wei, Xu De, A Review of Surface Defect Detection Methods Based on Deep Learning, 2021.05 (EI, selected as one of the top academic papers in "The Leader 5000 - China's Leading Journals") ）

[17]  Chandranath Adak , Tao X*, BigyaPAn: Deep Analysis of Old Paper Advertisement, IJCNN 2021: International Joint Conference on Neural Networks.  （EI）

[18]  Singh A K, Tao X. BCINet: An Optimized Convolutional Neural Network for EEG-Based Brain-Computer Interface Applications[C]//2020 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2020: 582-587. （EI）

[19]  Tao X*, Zhang D., Singh A. K., Prasad M., Lin C. T., Xu D. Weak Scratch Detection of Optical Components Using Attention Fusion Network[C]//2020 IEEE 16th International Conference on Automation Science and Engineering (CASE). IEEE, 2020: 855-862. （EI）

[20]  Hou W, Tao X*, Ma W, Xu D. SACNN: Spatial Adversarial Convolutional Neural Network for Textile Defect Detection[J]. Fibres & Textiles in Eastern Europe, 2020. （SCI）

[21]  Tao X*, Zhang D, Ma W, Liu X, Xu D. Automatic metallic surface defect detection and recognition with convolutional neural networks[J]. Applied Sciences, 2018, 8(9): 1575.  (SCI, google Scholar：201, web of science : 122, ESI Highly Cited Paper )

[22]  Tao X, Xu D, Zhang Z T, et al. Weak scratch detection and defect classification methods for a large-aperture optical element[J]. Optics Communications, 2017, 387: 390-400.（SCI）

​[1] Method, system, and device for analyzing the growth of defects on the surface of large diameter optical components, CN201910414436.8, first inventor.

[2] Method and device for automatic identification of defects in high-voltage transmission tower insulators, CN201810228904.8, first inventor

[3] Defect classification and identification method, device, computer device and storage medium, CN201811399279.X, first inventor.

[4] Method and apparatus for detecting and identifying surface defects of metal parts, CN201810228901.4, first inventor.

[5] Method for identifying defects in key components of high voltage transmission towers, CN201711182523.2, first inventor.

[6] Method and system for binarization of dark field images of scratches on the surface of large diameter optical components, CN201610894348.9, first inventor.

[7] A method and device for detecting optical surface defects by combining fine and coarse, CN201510779518.4, first inventor

[8] A scratch detection method and device for optical component surfaces, CN201510954616.7, first inventor.

[9] A method for generating a surface damage distribution map of a large diameter optical element, CN201410016315.5, first inventor.

[10] Method of connector assembly, CN202011606810.3, first inventor.

[11] Method, system and device for detecting weak scratches on optical components based on dark field images, CN201910955032.X, second inventor

[12] Device for surface inspection of large-diameter components and corresponding method for rapid damage location, CN201410041410.0, fourth inventor

[13] A high-resolution microscopic vision imaging device and control method, CN201410777930.8, fourth inventor.

[14] Microscopic vision-based method for detecting defects on the surface of white glass, CN201611092438.2, fourth inventor.

● 2nd in the vision defect detection task of “CVPR2023 VISION Data Challenge Competition Track 1- Data Efficient Defect Detection", Vancouver, Canada., May. 2023. 

 ● Most Innovative Solution in the vision defect detection task of “CVPR2023 VISION Data Challenge Competition Track 2- Data-generation for Defect Detection.", Vancouver, Canada., May. 2023. 

 ● Top-1%finalist in “The Alibaba Tianchi-Guangdong Industrial Intelligent Manufacturing Big Data Innovation Competition, Smart Algorithm Contest”, Aug. 2018.

● 2022 "Top Academic Papers of Leading Journals in China (F5000)" award. 

 ● Guest editor for the international journal “Sensors” (SCI, IF: 3.847). 

 ● Guest editor for the international journal “Electronics” (SCI, IF: 2.690) . 

 ● Guest editor for the international journal “Applied Sciences”(SCI, IF: 2.838) .

Venue: 2022 Global Artificial Intelligence Technology Conference (GAITC 2022), Hangzhou, China on 27st November, 2022 Title: “latest technological achievements in the field of industrial machine vision quality inspection”. 

 Venue: Third Industrial Machine Vision Technology Forum of the Chinese Computer Society (CCF) , Suzhou, China on September 17, 2021 Title: “ Industrial surface defect detection algorithm”. 

 Venue: JIS University in India on October 10, 2020 (presented virtually)

Computer Vision

Machine Vision and Intelligent Inspection

Precision Intelligent Assembly

Indian Institute of Technology Patna，India

University of Technology Sydney,   Australia

Zhen Qu

Shichen Qu

From August 1, 2022 to present,   IEEE Senior Member,

From November 29, 2020 to present,    Member of Intelligent Manufacturing Special Committee of China Automation Society

From October 30, 2020 to present,    Member of the Special Committee on Hybrid Intelligence of the Chinese Society of Automation

In 2019, the 14th "Chunhui Cup" Chinese Overseas Students Innovation and Entrepreneurship Competition won the High tech Group Award

In 2018, the CSC 'National Public Senior Researcher, Visiting Scholar, Postdoctoral' Program Scholarship for Studying Abroad