Welcome to Dawei Li’s Homepage!
Dawei Li 李大威PhD, Associate Professor Dean of Automation Department I am with the College of Information Sciences and Technology, the Engineering Research Center of Digitized Textile & Fashion Technology of Ministry of Education, and with the State Key Laboratory for Modification of Chemical Fibers and Polymer Materials (SKLFPM) Donghua University (211, Double First-Class) 2999 North Renmin Rd., Songjiang District, Shanghai, China 201620 Email: daweili[A.T.]dhu.edu.cn |
Academic History and Education Background:
I received B.E. in Automation in 2006 from Tongji University, Shanghai, China. During 2009-2010, I was a visiting researcher at Michigan State University, East Lansing, MI, USA. In 2013, I received the Ph.D. in Control Theory and Control Engineering from Tongji University, Shanghai, China. During 2013-2015, I was a postdoc at the Department of Computer Sciences and Technology, Tongji University, Shanghai, China. Currently an associate professor with Donghua University, Songjiang District, Shanghai, China.
Research Interests:
Image Processing, Point Cloud Processing, Artificial Intelligence, Intelligent Visual Surveillance, and Plant Phenotyping.
Teaching:
Semester A (Autumn):
1. Data Analysis and Machine Learning (for graduate students).
2. Pattern Recognition Principles and Techniques (for international students).
Semester B (Spring):
1. Digital Signal Processing (for undergraduates).
Research Projects and Talent Programs:
1. Shanghai Rising-Star Program, Person in Charge. (07/2021-06/2024).
2. “Research on the stereo imaging for plant phenotyping and genotype analysis”, Natural Science Foundation of Shanghai, Person in Charge. (07/2020-06/2023).
3. “3D imaging for analyzing the phenotypes of textile plants”, The Fundamental Research Funds for the Central Universities of China (special base project), Person in Charge. (01/2019-04/2020)
4. “Research of illumination-robust stereo vision algorithm for greenhouse plants”, National Natural Science Foundation of China, Person in Charge. (01/2017-12/2019).
5. Shanghai Sailing Program, Person in Charge. (06/2016-05/2019).
6. “Research on illumination-robust stereo vision imaging tools for greenhouse plants”, The Fundamental Research Funds for the Central Universities of China, Person in Charge. (01/2016-12/2018)
7. “A research on digitization and virtual visualization of greenhouse tomato plants”, China Postdoctoral Science Foundation Special Grants, Person in Charge. (07/2014-07/2015).
8. “Research on key technology in an intelligent video surveillance system”, Shanghai Yangpu District Innovation and Practice base project for postdocs, Person in Charge. (02/2014-12/2014).
9. “The research of digitized imaging and virtual visualization technologies on greenhouse plants”, China Postdoctoral Science Foundation 1st class grants, Person in Charge. (07/2013-12/2014).
Academic Participation:
1. Chinese Society of Agricultural Engineering, Senior Member.
2. Chinese Association of Automation, Member.
3. Shanghai Agricultural Engineering Association, Standing Director.
4. IEEE, Member.
5. IEEE CIS Shanghai Chapter, Secretary General.
6. Reviewer for a number of international conferences and journals including IEEE SPL, IEEE TCSVT, IEEE TMM, IEEE TCYB, IEEE ACCESS, IEEE RA-L, Graphics & Visual Computing, Plant Phenomics, Integrated Computer-Aided Engineering, Neurocomputing, IJPRAI, Applied Engineering in Agriculture (ASABE), Ecological Informatics, The Visual Computer, Automation in Construction, China Communications, International Journal of Remote Sensing, Scientific Programming, Frontiers in Plant Science, and NCAA.
Honors and Awards:
1. Best Paper Award for Young Researchers at The Annual Academic Conference of Chinese Society of Agricultural Engineering (3/4), Zhenjiang, China. (08/2013)
2. Best Doctoral Dissertation Award of Year 2013 (Top 28 among 592, 1/1), Tongji University, Shanghai, China. (05/2013)
3. Finalist for Best Paper Award (Top 6 among 899, 1/3) in the 11th International Conference on Control, Automation, Robotics and Vision (ICARCV2010), Singapore. (12/2010)
Selected Publications:
[1] D. Li†, L. Liu†, S. Xu, and S. Jin*, “TrackPlant3D: 3D organ growth tracking framework for organ-level dynamic phenotyping,” Computers and Electronics in Agriculture, 2024 (Minor Revision). (†Contributed equally)
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[2] D. Li†, Z. Zhou†, and Y. Wei, “Unsupervised shape-aware SOM down-sampling for plant point clouds,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 211, 2024, pp. 172-207. (†Contributed equally)
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[3] D. Li, Y. Wei, and R. Zhu, “A comparative study on point cloud down-sampling strategies for deep learning-based crop organ segmentation,” Plant Methods, vol. 19, Article No. 124, 2023.
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[4] D. Li, J. Li, S. Xiang, and A. Pan, “PSegNet: simultaneous semantic and instance segmentation for point clouds of plants,” Plant Phenomics, 2022, Article ID: 9787643.
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[5] D. Li†, F. Ahmed†, N. Wu, and A. I. Sethi, “YOLO-JD: A Deep Learning Network for Jute Diseases and Pests Detection from Images,” Plants, vol. 11, no. 7: 937, 2022. (†Contributed equally)
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[6] D. Li†, S. Wang†, S. Xiang, J. Li, Y. Yang, and X.-S. Tang, “Dual-stream shadow detection network – biologically inspired shadow detection for remote sensing images,” Neural Computing and Applications, vol. 34, 10039-10049, 2022. (†Contributed equally)
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[7] D. Li†, G. Shi†, J. Li, Y. Chen, S. Zhang, S. Xiang, and S. Jin, “PlantNet: A dual-function point cloud segmentation network for multiple plant species”, ISPRS Journal of Photogrammetry and Remote Sensing, vol. 184, 2022, pp. 243-263. (†Contributed equally)
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[8] X.-S. Tang, X. Xie, K. Hao, D. Li*, and M. Zhao, “A line-segment-based non-maximum suppression method for accurate object detection,” Knowledge-Based Systems, vol. 251, no. 5, 2022, 108885.
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[9] D. Li, G. Shi, Y. Wu, Y. Yang, and M. Zhao, “Multi-scale neighborhood feature extraction and aggregation for point cloud segmentation”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 6, 2021, pp. 2175-2191.
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[10] D. Li, S. Yan, M. Zhao, and T.W.S. Chow, “Spatiotemporal Tree Filtering for Enhancing Image Change Detection”, IEEE Transactions on Image Processing, vol. 29, pp. 8805-8820, 2020.
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[11] D. Li, S. Wang, X.-S. Tang, W. Kong, G. Shi, and Y. Chen, “Double-stream Atrous Network for Shadow Detection,” Neurocomputing, vol. 317, 2020, pp. 167-175.
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[12] D. Li, G. Shi, W. Kong, S. Wang, and Y. Chen, “A leaf segmentation and phenotypic feature extraction framework for Multi-View Stereo plant point clouds,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, 2020, pp. 2321-2336.
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[13] D. Li, Y. Cao, G. Shi, X. Cai, Y. Chen, S. Wang, and S. Yan, “An overlapping-free leaf segmentation method for plant point clouds,” IEEE Access, vol. 7, no. 9, pp. 129054-129070, 2019.
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[14] D. Li, S. Yan, X. Cai, Y. Cao, and S. Wang, “An Integrated image filter for enhancing change detection results,” IEEE Access, vol. 7, no. 1, pp. 91034-91051, 2019.
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[15] D. Li, Y. Cao, X.-S. Tang, S. Yan, and X. Cai, “Leaf Segmentation on Dense Plant Point Clouds with Facet Region Growing,” Sensors, vol. 18, no. 11, Article 3625, 2018.
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[16] D. Li, L. Xu, X. Tang, S. Sun, X. Cai, and P. Zhang, “3D Imaging of Greenhouse Plants with an Inexpensive Binocular Stereo Vision System,” Remote Sensing, vol. 9, no. 5, Article 508, 2017.
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[17] D. Li, L. Xu, and H. Liu, “Detection of Uneaten Fish Food Pellets in Underwater Images for Aquaculture,” Aquacultural Engineering, vol. 78, Part B, pp. 85-94, 2017.
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[18] Y. Su, L. Xu, and D. Li, “Adaptive Fuzzy Control of a Class of MIMO Nonlinear System with Actuator Saturation for Greenhouse Climate Control Problem,” IEEE Transactions on Automation Science and Engineering, vol. 13, no. 2, 2016, pp. 772-788.
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[19] D. Li, L. Xu, C. Tan, E.D. Goodman, D. Fu, and L. Xin, “Digitization and Visualization of Greenhouse Tomato Plants in Indoor Environments,” Sensors, vol. 15, no. 2, 2015, pp. 4019-4051.
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[20] D. Li, L. Xu, and E. Goodman, “On-line EM Variants for Multivariate Normal Mixture Model in Background Learning and Moving Foreground Detection,” Journal of Mathematical Imaging and Vision, vol. 48, no. 1, 2014, pp. 114-133.
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[21] D. Li, L. Xu, and E. Goodman, “Illumination-robust Foreground Detection in a Video Surveillance System,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 10, pp. 1637-1650, 2013.
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[22] D. Li, L. Xu, E. Goodman, Y. Xu, and W. Yang, “Integrating a statistical background-foreground extraction algorithm and SVM classifier for pedestrian detection and tracking”, Integrated Computer-Aided Engineering, vol. 20, no.3, 2013, pp. 201-216.
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[23] D. Li, L. Xu, and E. Goodman, “Online Background Learning for Illumination-robust Foreground Detection,” in: Proc. 11th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2010, pp. 1093-1100. (Finalist for Best Paper Award)
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