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Minh Dao

2 accepted papers

2015

Hierarchical Sparse and Collaborative Low-Rank representation for emotion recognition

ICASSP 2015accepted

In this paper, we design a Collaborative-Hierarchical Sparse and Low-Rank (C-HiSLR) model that is natural for recognizing human emotion in visual data. Previous attempts require explicit expression components, which are often unavailable and difficult to recover. Instead, our model exploits the low-…

Cited by 0SourceScholar
2015

Multi-sensor classification via sparsity-based representation with low-rank interference

ICASSP 2015accepted

In this paper, we propose a general collaborative sparse representation framework for multi-sensor classification which exploits correlation as well as complementary information among homogeneous and heterogeneous sensors while simultaneously extracting the low-rank interference term. Specifically,…

Cited by 0SourceScholar