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Sparse coding with unity range codes and label consistent discriminative dictionary learning

Nilsson, Mikael LU (2017) 2016 23rd International Conference on Pattern Recognition (ICPR 2016) p.3186-3191
Abstract

A novel sparse coding framework with unity range codes and the possibility to produce a discriminative dictionary is presented. The framework is, in contrast to many other works, able to handle unsupervised, supervised and semi-supervised settings. Furthermore, codes are constrained to be in unity range, which is beneficial in many scenarios. The paper presents the framework and solvers used to produce dictionaries and codes. Experiments in image reconstruction and feature learning for classification highlight the benefits with the proposed framework.

Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2016 23rd International Conference on Pattern Recognition, ICPR 2016
article number
7900125
pages
6 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2016 23rd International Conference on Pattern Recognition (ICPR 2016)
conference location
Cancún, Mexico
conference dates
2016-12-04 - 2016-12-08
external identifiers
  • scopus:85019149596
ISBN
9781509048472
DOI
10.1109/ICPR.2016.7900125
language
English
LU publication?
yes
id
4a2e9e1b-b1c2-4525-82ef-82c0829cd315
date added to LUP
2017-06-02 12:51:37
date last changed
2022-01-30 20:39:00
@inproceedings{4a2e9e1b-b1c2-4525-82ef-82c0829cd315,
  abstract     = {{<p>A novel sparse coding framework with unity range codes and the possibility to produce a discriminative dictionary is presented. The framework is, in contrast to many other works, able to handle unsupervised, supervised and semi-supervised settings. Furthermore, codes are constrained to be in unity range, which is beneficial in many scenarios. The paper presents the framework and solvers used to produce dictionaries and codes. Experiments in image reconstruction and feature learning for classification highlight the benefits with the proposed framework.</p>}},
  author       = {{Nilsson, Mikael}},
  booktitle    = {{2016 23rd International Conference on Pattern Recognition, ICPR 2016}},
  isbn         = {{9781509048472}},
  language     = {{eng}},
  month        = {{04}},
  pages        = {{3186--3191}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Sparse coding with unity range codes and label consistent discriminative dictionary learning}},
  url          = {{http://dx.doi.org/10.1109/ICPR.2016.7900125}},
  doi          = {{10.1109/ICPR.2016.7900125}},
  year         = {{2017}},
}