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Feature fusion based on joint sparse representations and wavelets for multiview classification

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Bibliographic Details
Main Authors: Younes, Akbari, Omar, Elharrouss, Somaya, Al-Maadeed
Format: Book
Language:English
Published: Springer 2023
Subjects:
Feature fusion
multiview classification
Online Access:https://link.springer.com/article/10.1007/s10044-022-01110-2
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8290
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spelling oai:localhost:PNK-82902023-04-25T07:29:15Z Feature fusion based on joint sparse representations and wavelets for multiview classification Younes, Akbari Omar, Elharrouss Somaya, Al-Maadeed Feature fusion multiview classification CC BY Feature-level-based fusion has attracted much interest. Generally, a dataset can be created in different views, features, or modalities. To improve the classification rate, local information is shared among different views by various fusion methods. However, almost all the methods use the views without considering their common aspects. In this paper, wavelet transform is considered to extract high and low frequencies of the views as common aspects to improve the classification rate. The fusion method for the decomposed parts is based on joint sparse representation in which a number of scenarios can be considered. The presented approach is tested on three datasets. The results obtained by this method prove competitive performance in terms of the datasets compared to the state-of-the-art results. 2023-04-25T07:29:15Z 2023-04-25T07:29:15Z 2022 Book https://link.springer.com/article/10.1007/s10044-022-01110-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8290 en application/pdf Springer
institution Digital Phenikaa
collection Digital Phenikaa
language English
topic Feature fusion
multiview classification
spellingShingle Feature fusion
multiview classification
Younes, Akbari
Omar, Elharrouss
Somaya, Al-Maadeed
Feature fusion based on joint sparse representations and wavelets for multiview classification
description CC BY
format Book
author Younes, Akbari
Omar, Elharrouss
Somaya, Al-Maadeed
author_facet Younes, Akbari
Omar, Elharrouss
Somaya, Al-Maadeed
author_sort Younes, Akbari
title Feature fusion based on joint sparse representations and wavelets for multiview classification
title_short Feature fusion based on joint sparse representations and wavelets for multiview classification
title_full Feature fusion based on joint sparse representations and wavelets for multiview classification
title_fullStr Feature fusion based on joint sparse representations and wavelets for multiview classification
title_full_unstemmed Feature fusion based on joint sparse representations and wavelets for multiview classification
title_sort feature fusion based on joint sparse representations and wavelets for multiview classification
publisher Springer
publishDate 2023
url https://link.springer.com/article/10.1007/s10044-022-01110-2
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8290
_version_ 1764177438493900800
score 8.887836

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