PLSA-Based Sparse Representation for Object Classification

Abstract

This paper proposes a novel object classification method which uses the concept of probabilistic latent semantic analysis (pLSA) to overcome the problem of sparse representation in data classification. Sparse representation is widely used and quite successful in many vision-based applications. However, it needs to calculate the sparse reconstruction cost… (More)
DOI: 10.1109/ICPR.2014.232

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Cite this paper

@article{Yan2014PLSABasedSR, title={PLSA-Based Sparse Representation for Object Classification}, author={Yilin Yan and Jun-Wei Hsieh and Hui-Fen Chiang and Shyi-Chyi Cheng and Duan-Yu Chen}, journal={2014 22nd International Conference on Pattern Recognition}, year={2014}, pages={1295-1300} }