A multi-class structured dictionary learning method using discriminant atom selection-Reference-Cited by-同舟云学术

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A multi-class structured dictionary learning method using discriminant atom selection

Published:2020-11-19 Issue:2 Volume:24 Page:685-700
ISSN:1433-7541
Container-title:Pattern Analysis and Applications
language:en
Short-container-title:Pattern Anal Applic

Author:

Rolon Roman E.^ORCID,Di Persia Leandro E.^ORCID,Spies Ruben D.^ORCID,Rufiner Hugo L.^ORCID

Funder

Fondo para la Investigación Científica y Tecnológica

Universidad Nacional del Litoral

Consejo Nacional de Investigaciones Científicas y Técnicas

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition

Link

https://link.springer.com/content/pdf/10.1007/s10044-020-00939-9.pdf

Reference37 articles.

1. Rolon R, Larrateguy L, Persia LD, Spies R, Rufiner H (2017) Discriminative methods based on sparse representations of pulse oximetry signals for sleep apnea-hypopnea detection. Biomed Signal Process Control 33:358–367

2. Peterson V, Rufiner HL, Spies RD (2017) Generalized sparse discriminant analysis for event-related potential classification. Biomed Signal Process Control 35:70–78

3. Li L, Li S, Fu Y (2014) Learning low-rank and discriminative dictionary for image classification. Image Vis Comput 32(10):814–823

4. Mairal J, Bach F, Ponce J, Sapiro G, Zisserman A (2008) Discriminative learned dictionaries for local image analysis. In: 2008 IEEE conference on computer vision and pattern recognition, pp 1–8

5. Elad M, Aharon M (2006) Image denoising via sparse and redundant representations over learned dictionaries. IEEE Trans Image Process 15(12):3736–3745

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Distributed Dictionary Learning Over Heterogeneous Clients Using Local Adaptive Dictionaries;2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP);2021-10-25

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