Sparse representation for machine learning has been exploited in past years. Several sparse representation based classification algorithms have been developed for some application...
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
Abstract. This paper proposes a novel method to deal with the representation issue in texture classification. A learning framework of image descriptor is designed based on the Fish...
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the IterationTuned and Aligned Dictionary (ITAD). The quest...