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professor at Universiti Malaya



Google Scholar | [Curriculum Vitae]
Follow @cs-chan

My research interests include computer vision and machine learning, where I lead a research team that has published more than 100 papers in related top peer-review conferences and journals (e.g. CVPR, NeurIPS, TPAMI, TIP etc). I was the founding Chair for IEEE Computational Intelligence Society, Malaysia chapter.

Also currently, I serve as the Associate Editor of Pattern Recognition (Elsevier), and have co-organized several conferences/workshops/tutorials/challenges related to computer vision/machine learning. I am a Senior Member of IEEE, a Chartered Engineer and a Member of IET.

From 2020-2022, I am seconded to the Ministry of Science, Technology and Innovation (MOSTI) as the Undersecretary for Division of Data Strategic and Foresight, as well as the Lead of PICC Unit under COVID19 Immunisation Task Force (CITF).

Highlights:
        03/2022: One(1) paper to appear in ICPR-2022.

I am always interested to hear from prospective research students. Scholarships are available from time to time, contact me to enquire.


Latest Works

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Extremely Low-light Image Enhancement with Scene Text Restoration

This work deals with the problem of low-light image enhancement, in the context of scene texts.

P. Hsu, C-T. Lin, C.C. Ng, J-L. Kew, M.Y. Tan, S-H. Lai, C.S. Chan and C. Zach
ICPR 2022
[pdf] [code (coming soon)]

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One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective Star

This paper proposes a novel deep hashing model with only a single learning objective which is a simplification from most state of the art papers generally use lots of losses and regularizer.

J.T. Hoe, K.W. Ng, T. Zhang, C.S. Chan, Y-Z. Song and T. Xiang
NeurIPS 2021 (acceptance rate: 2372/9122 ~ 26.0%)
[pdf] [code]

2

DeepIP: Deep Neural Network Intellectual Property Protection with Passports Star

We propose novel passport-based DNN ownership verification schemes which are both robust to network modifications and resilient to ambiguity attacks (i.e. the DNN model performance of an original task will be significantly deteriorated due to forged passports). Extension of NeurIPS 2019 (acceptance rate: 1428/6743 ~ 21.18%).

L. Fan, K.W. Ng, C.S. Chan and Q. Yang
IEEE Transactions on Pattern Analysis and Machine Intelligence (in Press)
[pdf] [code]

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Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attacks Star

This paper presents a complete protection framework in both black-box and white-box settings to enforce IPR protection on GANs.

D.S. Ong, C.S. Chan, K.W. Ng, L. Fan and Q. Yang.
CVPR 2021 (acceptance rate: 1663/7015 ~ 23.7%)
[pdf] [code]