.png){kind=icon}
返回
Simultaneous dimensionality reduction and dictionary learning for sparse representation based classification
.png){kind=icon}
PRE
AI
DOI：10.1007/s11042-016-3492-1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Learning dictionaries from the training data has led to promising results for pattern classification tasks. Dimensionality reduction is also an important issue for pattern classification. However, most existing methods perform dimensionality reduction (DR) and dictionary learning (DL) independently, which may result in not fully exploiting the discriminative information of the training data. In this paper, we propose a simultaneous dimensionality reduction and dictionary learning (SDRDL) model to learn a DR projection matrix and a class-specific dictionary (i.e., the dictionary atoms correspond to the class labels) simultaneously. Since simultaneously learning makes the learned projection and dictionary fit better with each other, more effective pattern classification can be achieved using the representation residual. In SDRDL model, not only the representation residual is discriminative, but the representation coefficients are also discriminative. Therefore, a classification scheme associated with SDRDL is presented by exploiting such discriminative information. Experimental results on a series of benchmark image databases show that our proposed method outperforms many state-of-the-art discriminative dictionary learning methods.
Keyword:
Dictionary learning
Sparse representation
Dimensionality reduction
Image classification
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3
论文数:
1.9W
被引数:
3.2W
机构
引用论文
Sparse Representation Based Fisher Discrimination Dictionary Learning for Image Classification基于稀疏表示的Fisher判别字典学习图像分类
.png){kind=icon}
PREAI
分享收藏A micromachined efficient parametric array loudspeaker with a wide radiation frequency band具有宽辐射频带的微机械高效参量阵列扬声器
PREAI
分享收藏
Image denoising via sparse and redundant representations over learned dictionaries通过学习字典上的稀疏和冗余表示进行图像去噪
PREAI
分享收藏
查看更多内容