Hierarchical Discriminative Deep Dictionary Learning

被引:9
作者
Rodriguez-Dominguez, Ulises [1 ]
Dalmau, Oscar [1 ]
机构
[1] Math Res Ctr, Guanajuato 36023, Mexico
关键词
Dictionaries; Machine learning; Proposals; Training; Transforms; Encoding; Neural networks; Dictionary learning; machine learning; image classification; neural network; ROBUST FACE RECOGNITION; LOW-RANK; ALGORITHM;
D O I
10.1109/ACCESS.2020.3008841
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In deep dictionary learning multiple dictionaries are learned based on information at various levels of abstraction. We propose a novel hierarchical discriminative dictionary learning layer embedded within a neural network with an image classification objective. Discrimination is induced in the learned synthesis dictionaries at multiple hierarchical levels in a simple way by a one-hot-code representation of the class labels during the training backward pass. In addition, local sparse representation objectives are approximated during the forward pass, introducing local regularization. We evaluate our proposal on five known datasets and we either outperform state-of-the-art methods or achieve competitive classification results.
引用
收藏
页码:142680 / 142690
页数:11
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