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- Title
Elastic net regularized dictionary learning for image classification.
- Authors
Shen, Bin; Liu, Bao-Di; Wang, Qifan
- Abstract
Dictionary learning plays a key role in image representation for classification. A multi-modal dictionary is usually learned from feature samples across different classes and shared in the feature encoding process. Ideally each atom in dictionary corresponds to a single class of images, while each class of images corresponds to a certain group of atoms. Image features are encoded as linear combinations of selected atoms in a given dictionary. We propose to use elastic net as regularizer to select atoms in feature coding and related dictionary learning process, which not only benefits from the sparsity similar as ℓ penalty but also encourages a grouping effect that helps improve image representation. Experimental results of image classification on benchmark datasets show that with dictionary learned in the proposed way outperforms state-of-the-art dictionary learning algorithms.
- Subjects
MATHEMATICAL regularization; DATA dictionaries; IMAGE analysis; LEARNING classifier systems; SPARSE graphs
- Publication
Multimedia Tools & Applications, 2016, Vol 75, Issue 15, p8861
- ISSN
1380-7501
- Publication type
Article
- DOI
10.1007/s11042-014-2257-y