S
Shuicheng Yan
Researcher at National University of Singapore
Publications - 827
Citations - 78145
Shuicheng Yan is an academic researcher from National University of Singapore. The author has contributed to research in topics: Feature extraction & Facial recognition system. The author has an hindex of 123, co-authored 810 publications receiving 66192 citations. Previous affiliations of Shuicheng Yan include Nanjing University of Science and Technology & University of Science and Technology of China.
Papers
More filters
Posted Content
Network In Network
Min Lin,Qiang Chen,Shuicheng Yan +2 more
TL;DR: With enhanced local modeling via the micro network, the proposed deep network structure NIN is able to utilize global average pooling over feature maps in the classification layer, which is easier to interpret and less prone to overfitting than traditional fully connected layers.
Journal ArticleDOI
Face recognition using Laplacianfaces
TL;DR: Experimental results suggest that the proposed Laplacianface approach provides a better representation and achieves lower error rates in face recognition.
Journal ArticleDOI
Robust Recovery of Subspace Structures by Low-Rank Representation
TL;DR: It is shown that the convex program associated with LRR solves the subspace clustering problem in the following sense: When the data is clean, LRR exactly recovers the true subspace structures; when the data are contaminated by outliers, it is proved that under certain conditions LRR can exactly recover the row space of the original data.
Journal ArticleDOI
Graph Embedding and Extensions: A General Framework for Dimensionality Reduction
TL;DR: A new supervised dimensionality reduction algorithm called marginal Fisher analysis is proposed in which the intrinsic graph characterizes the intraclass compactness and connects each data point with its neighboring points of the same class, while the penalty graph connects the marginal points and characterizing the interclass separability.
Proceedings Article
Network In Network
Min Lin,Qiang Chen,Shuicheng Yan +2 more
TL;DR: In this paper, a Network in Network (NIN) architecture is proposed to enhance model discriminability for local patches within the receptive field, where the feature maps are obtained by sliding the micro networks over the input in a similar manner as CNN, and then fed into the next layer.