Dictionary learning based on discriminative energy contribution for image classification
作者：
Highlights：
• Learn a dictionary based on discriminative energy contribution for image classification.
• A linear classifier is designed in dictionary learning process for efficient classification.
• The ℓ2 norm-based dictionary learning benefits for convenient computation.
• DECDL fulfills the classification task with small number of training samples.
• Experiments on the face/texture databases verify that DECDL outperforms the state-of-the-art methods.
摘要
• Learn a dictionary based on discriminative energy contribution for image classification.• A linear classifier is designed in dictionary learning process for efficient classification.• The ℓ2 norm-based dictionary learning benefits for convenient computation.• DECDL fulfills the classification task with small number of training samples.• Experiments on the face/texture databases verify that DECDL outperforms the state-of-the-art methods.
论文关键词：Image classification,Dictionary learning,Discriminative energy contribution,Linear classifier
论文评审过程：Received 17 October 2015, Revised 17 September 2016, Accepted 20 September 2016, Available online 21 September 2016, Version of Record 20 October 2016.
论文官网地址：https://doi.org/10.1016/j.knosys.2016.09.018
