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Li CHENG
Principal Investigator, group head
Machine Learning For Bioimage Analysis Group
chengli@bii.a-star.edu.sg
Office: (+65) 64788358; mobile:
91577574
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What's new |
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[new!] Our group has an opening for
a Postdoc researcher in Computer Vision and Machine
Learning. |
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Biography |
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CHENG,
Li is a research scientist and group leader at
Bioinformatics Institute (BII). Prior to joining BII July
of 2010, He worked at Statistical Machine Learning group of
NICTA, Australia, TTI-Chicago, USA, and University of Alberta,
Canada, where he obtained his Ph.D.in Computer Science. His
research expertise is mainly on machine learning and computer
vision. He is a senior member of IEEE. |
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For Potential Graduate Students
and Interns |
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I
am always looking for self-motivated students with a
strong computer science and engineering background who
are interested to work with me. Possible research
topics include machine learning or computer vision for
addressing biological, medical, and public
health problems.
PhD applications should come through the SINGA or the
AGS PhD programs from National University of Singapore (or
Nanyang Technological University). Students from
China may also consider the China
Scholarship Council (CSC) award.
Short time (3-6 months) research internship is also
possible through various funding sources. Please contact
me regarding current opportunities.
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Projects
(about SVN projects)
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Our Weekly Reading Group
(
on Machine Learning and Computer Vision)
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Selected
Publications (full
list)
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- Xiaowei Zhang, Xudong Shi, Yu Sun, Li
Cheng. Multivariate Regression with Gross Errors on
Manifold-valued Data. In IEEE Trans. Pattern Analysis and
Machine Intelligence (TPAMI), 2017.
Project Webpage
Details BibTeX Download: [pdf]
- Jaydeep De, Xiaowei Zhang, Feng Lin, Li
Cheng. Transduction on Directed Graphs via Absorbing Random
Walks. In IEEE Trans. Pattern Analysis and Machine
Intelligence (TPAMI), 2017.
Project Webpage
Details BibTeX Download: [pdf]
- Chi Xu, Lakshmi Narasimhan Govindarajan, Yu
Zhang, Li Cheng. Lie-X: Depth Image Based Articulated Object
Pose Estimation, Tracking, and Action Recognition on Lie
Groups. In International Journal of Computer Vision
(IJCV), 123(3):454-478, 2017.
Project Webpage
Details BibTeX Download: [pdf]
- GU Lin, Xiaowei Zhang, He Zhao, Huiqi Li,
and Li Cheng. Segment 2D and 3D Filaments by Learning Structured
and Contextual Features. In IEEE Trans. Medical Imaging
(TMI),36(2):569-606, 2017.
Project Webpage
Details BibTeX Download: [pdf]
- Chi Xu, Lilian Zhang, Li Cheng, Reinhard
Koch. Pose Estimation from Line Correspondences: A Complete
Analysis and A Series of Solutions. In IEEE Trans. Pattern
Analysis and Machine Intelligence (PAMI),39(6):1209-22,
2017.
Details BibTeX Download: [pdf]
- Adam Cliffe, David P. Doupe, HsinHo Sung,
Isaac Lim Kok Hwee, Li Cheng, Kok Haur Ong, and Weimiao Yu.
Quantitative 3D analysis of complex single border cell behaviors
in coordinated collective cell migration. In Nature
Communications, 14905:1-13, 2017.
Details BibTeX Download: [pdf]
- Xiaowei Zhang, Li Cheng, Delin Chu, Li-Zhi
Liao, Michael Ng, Roger C.E. Tan. Incremental Regularized Least
Squares for Dimensionality Reduction of Large-Scale Data. In
SIAM Journal on Scientific Computing, 38(3):414-39,
2016.
Details BibTeX Download: [pdf]
- Li Liu, Li Cheng, Ye Liu, Yongpo Jia, David
Rosenblum. Recognizing Complex Activities by a Probabilistic
Interval-Based Model. In National Conference on Artificial
Intelligence (AAAI), 2016.
Details BibTeX Download: [pdf]
- Chi Xu, Ashwin Nanjappa, Xiaowei Zhang, Li Cheng.
Estimate Hand Poses Efficiently from Single Depth Images. In
International Journal of Computer Vision (IJCV),
(116)1:21-45, 2016.
Project Webpage, dataset and online performance
Evaluation
Details BibTeX Download: [pdf]
- Jaydeep De, Li Cheng, Xiaowei Zhang, Feng
Lin, Huiqi Li, Kok Haur Ong, Weimiao Yu, Yuanhong Yu, Sohail Ahmed.
A Graph-theoretical Approach for Tracing Filamentary Structures
in Neuronal and Retinal Images. In IEEE Trans. Medical
Imaging (TMI), (35)1:252-72, 2016.
Project Webpage
Details BibTeX Download: [pdf]
- Lin Gu, Li Cheng. Learning to Boost Filamentary
Structure Segmentation. In International Conference on
Computer Vision (ICCV), 2015.
Project Webpage
Details BibTeX Download: [pdf]
- Minglun Gong, Yiming Qian, Li Cheng.
Integrated Foreground Segmentation and Boundary Matting for Live
Videos. In IEEE Trans. Image Processing (TIP),
24(4):1356-70, 2015.
Details BibTeX Download: [pdf]
- Li Cheng, Sinno Jialin Pan.
Semi-supervised Domain Adaptation on Manifolds. In IEEE
Transactions on Neural Networks and Learning Systems (TNNLS),
25(12):2240-9, 2014.
Details BibTeX Download: [pdf]
- Li Cheng, Jaydeep De,
Xiaowei Zhang, Feng Lin, Huiqi Li. Tracing Retinal Blood Vessels
by Matrix-Forest Theorem of Directed Graphs. In MICCAI,
2014.
Project Webpage
Details BibTeX Download:
[pdf]
- Chi Xu, Li Cheng.
Efficient Hand Pose Estimation from a Single Depth Image. In
International Conference on Computer Vision (ICCV),
2013.
Project Webpage
Details BibTeX Download: [pdf]
- Li Cheng. Riemannian
Similarity Learning. In International Conference on Machine
Learning (ICML), 2013.
Details BibTeX Download: [pdf]
- Li Cheng, Ning Ye, Weimiao Yu, Andre
Cheah. Discriminative Cellular Segmentation for Microscopic
Images. In Medical Image Computing and Computer Assisted
Intervention (MICCAI), 2011.
Details BibTeX Download:
[pdf]
- Qinfeng Shi, Li Wang, Li Cheng, and
Alex Smola. Discriminative Human Action Segmentation and
Recognition using SMMs. In International Journal of
Computer Vision (IJCV), 93(1):22-32, 2011.
Code and Syn Data
Details BibTeX
Download: [pdf]
- Minglun
Gong, Li Cheng. Foreground Segmentation of Live Videos
using Locally Competing 1SVMs. In IEEE Conference on
Computer Vision and Pattern Recognition (CVPR), 2011.
Details BibTeX
Download: [pdf]
- Li Cheng, M. Gong, D.
Schuurmans, and T. Caelli. Real-time Discriminative
Background Subtraction. IEEE Trans. Image
Processing, 20(5), 1401-1414, 2011.
Project Webpage
Details BibTeX
- Li Cheng, Minglun Gong. Realtime Background
Subtraction from Dynamic Scenes. In IEEE International
Conference on Computer Vision (ICCV), 2009.
Details BibTeX Download: [pdf]
- Tiberio
Caetano, Julian McAuley, Li Cheng, Quoc Le, and Alex Smola.
Learning Graph Matching. IEEE Trans. Pattern Analysis and
Machine Intelligence (PAMI), 31(6):1048-1058, 2009.
Details BibTeX
- Li Cheng, S.V.N.
Vishwanathan, and Xinhua Zhang. Consistent image analogies using
semi-supervised learning. In IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), 2008.
Details BibTeX Download:
[pdf]
- Jun Zhou, Li Cheng, and
Walter Bischof. Prediction and Change Detection In Sequential
Data for Interactive Applications. In National Conference on
Artificial Intelligence (AAAI), pp. 805--810, AAAI, 2008.
Details BibTeX Download:
[pdf]
- Li Cheng and S.V.N.
Vishwanathan. Learning to compress images and videos. In
Proceedings of the 24th international conference on Machine
learning (ICML), pp. 161--168, ACM, New York, NY, USA,
2007.
Details BibTeX Download: [pdf]
- Li Cheng, S.V.N.
Vishwanathan, Dale Schuurmans, Shaojun Wang, and Terry Caelli.
implicit Online Learning with Kernels. In B. Scholkopf, J.
Platt, and T. Hoffman, editors, Advances in Neural Information
Processing Systems (NIPS), pp. 249--256, MIT Press, Cambridge,
MA, 2007.
Details BibTeX
Download:
[pdf]
- Li Cheng and
Terry Caelli. Bayesian stereo matching. Computer Vision
and Image Understanding (CVIU), 106(1):85--96, 2007.
Details BibTeX Download: [pdf]
- Jun Zhou, Li
Cheng, and Walter Bischof. Online Learning with Novelty
Detection in Human-guided Road Tracking. IEEE Transactions
on Geoscience and Remote Sensing, 45(12):3967--3977,
2007.
Details BibTeX Download:
[HTML]
- Li Cheng and Terry Caelli.
Component Optimization for Image Understanding: a Bayesian
Approach. IEEE Trans. Pattern Analysis and Machine
Intelligence (PAMI), 28(5):684--693, 2006.
Details BibTeX Download: [HTML]
- Li Cheng, Feng Jiao, Dale
Schuurmans, and Shaojun Wang. Variational Bayesian image
modelling. In Proceedings of the 22nd international
conference on Machine learning (ICML), pp. 129--136, ACM, New
York, NY, USA, 2005.
Details BibTeX Download:
[pdf]
- Shaojun Wang, Shaomin Wang,
Russ Greiner, Dale Schuurmans, and Li Cheng. Exploiting
syntactic, semantic and lexical regularities in language modeling
via directed Markov random fields. In Proceedings of the
22nd international conference on Machine learning (ICML), pp.
948--955, ACM, New York, NY, USA, 2005.
Details BibTeX
Download:
[pdf]
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3,76></ |