PR

Elsevier Journal of Pattern Recognition

Discriminative Feature Learning from Big Data for Visual Recognition

This special issue aims to solicit recent state-of-the-art achievements from both industry and academia on how to effectively learn discriminative visual features from big data for visual recognition. Of particular interest are submissions in (but not limited to) the following areas:
1) Sparse representation and its related applications
2) Dictionary learning and its related applications
3) Deep learning and its related applications
4) Matrix factorization and its related applications
5) Nonlinear embeddings and its related applications
6) Binary code learning and its related applications
7) Submodularity-based feature selection and its related applications

Important Dates:
• Paper submission due: Sep. 30, 2014
• First notification: Dec. 30, 2014

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