Search Results for author: Tsung-Han Chan

Found 8 papers, 1 papers with code

Semiblind Hyperspectral Unmixing in the Presence of Spectral Library Mismatches

no code implementations7 Jul 2015 Xiao Fu, Wing-Kin Ma, José Bioucas-Dias, Tsung-Han Chan

The dictionary-aided sparse regression (SR) approach has recently emerged as a promising alternative to hyperspectral unmixing (HU) in remote sensing.

Hyperspectral Unmixing regression

Robust Face Recognition by Constrained Part-based Alignment

no code implementations20 Jan 2015 Yuting Zhang, Kui Jia, Yueming Wang, Gang Pan, Tsung-Han Chan, Yi Ma

By assuming a human face as piece-wise planar surfaces, where each surface corresponds to a facial part, we develop in this paper a Constrained Part-based Alignment (CPA) algorithm for face recognition across pose and/or expression.

Face Alignment Face Recognition +1

Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search are Related

no code implementations15 Sep 2014 Xiao Fu, Wing-Kin Ma, Tsung-Han Chan, José M. Bioucas-Dias

We then perform exact recovery analyses, and prove that the proposed greedy algorithm is robust to noise---including its identification of the (unknown) number of endmembers---under a sufficiently low noise level.

Hyperspectral Unmixing regression

DL-SFA: Deeply-Learned Slow Feature Analysis for Action Recognition

no code implementations CVPR 2014 Lin Sun, Kui Jia, Tsung-Han Chan, Yuqiang Fang, Gang Wang, Shuicheng Yan

In this paper, we propose to combine SFA with deep learning techniques to learn hierarchical representations from the video data itself.

Action Recognition

PCANet: A Simple Deep Learning Baseline for Image Classification?

2 code implementations14 Apr 2014 Tsung-Han Chan, Kui Jia, Shenghua Gao, Jiwen Lu, Zinan Zeng, Yi Ma

In this work, we propose a very simple deep learning network for image classification which comprises only the very basic data processing components: cascaded principal component analysis (PCA), binary hashing, and block-wise histograms.

Classification Face Recognition +5

Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment

no code implementations8 Feb 2014 Liansheng Zhuang, Tsung-Han Chan, Allen Y. Yang, S. Shankar Sastry, Yi Ma

In particular, the single-sample face alignment accuracy is comparable to that of the well-known Deformable SRC algorithm using multiple gallery images per class.

Face Alignment Face Recognition +1

Learning by Associating Ambiguously Labeled Images

no code implementations CVPR 2013 Zinan Zeng, Shijie Xiao, Kui Jia, Tsung-Han Chan, Shenghua Gao, Dong Xu, Yi Ma

Our framework is motivated by the observation that samples from the same class repetitively appear in the collection of ambiguously labeled training images, while they are just ambiguously labeled in each image.

Association

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