Zobrazeno 1 - 10
of 100
pro vyhledávání: '"Marie Luong"'
Publikováno v:
IEEE Access, Vol 10, Pp 31548-31560 (2022)
In this study, we propose a novel sparse representation learning method in the Quaternion Wavelet (QW) domain for multi-class image classification. The proposed method takes advantages from: i) the QW decomposition, which promotes sparsity and provid
Externí odkaz:
https://doaj.org/article/b2f01025d5974959a30d9fa1fe83070f
Publikováno v:
Signal, Image and Video Processing. 16:1721-1729
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f924b5cdf638d74b1e9bf40307f0933a
https://doi.org/10.1007/s11760-021-02112-z
https://doi.org/10.1007/s11760-021-02112-z
Publikováno v:
2022 9th NAFOSTED Conference on Information and Computer Science (NICS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a2867e9456bad0978bc11248935c673
https://doi.org/10.1109/nics56915.2022.10013403
https://doi.org/10.1109/nics56915.2022.10013403
Publikováno v:
2022 IEEE International Conference on Image Processing (ICIP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5f2399d8463fbe882b5dd757a46a2c88
https://doi.org/10.1109/icip46576.2022.9897302
https://doi.org/10.1109/icip46576.2022.9897302
Publikováno v:
Pattern Recognition. 135:109155
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43f5cbdab1d1e63be70f1d4a37861780
https://doi.org/10.1016/j.patcog.2022.109155
https://doi.org/10.1016/j.patcog.2022.109155
How to reduce dose radiation while preserving the image quality as when using standard dose is one of the most important topics in the Computed Tomography (CT) imaging domain due to quality of low dose CT (LDCT) images is often strongly affected by n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::038d26cf5933b193b5ead29b09bcf5de
https://doi.org/10.36227/techrxiv.16910395
https://doi.org/10.36227/techrxiv.16910395
Publikováno v:
MMSP
In this paper, we propose an effective Convolutional Autoencoder (AE) model for Sparse Representation (SR) in the Wavelet Domain for Classification (SRWC). The proposed approach involves an autoencoder with a sparse latent layer for learning sparse c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bec79cb4cea8f40e6adf0734f9b7e79d
https://doi.org/10.1109/mmsp48831.2020.9287107
https://doi.org/10.1109/mmsp48831.2020.9287107
Publikováno v:
REV Journal on Electronics and Communications. 9
X-ray computed tomography (CT) is now a widely used imaging modality for numerous medical purposes. The risk of high X-ray radiation may induce genetic, cancerous and other diseases, demanding the development of new image processing methods that are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6306368f44e3502333a51fee13c0e7b0
https://doi.org/10.21553/rev-jec.238
https://doi.org/10.21553/rev-jec.238
Autor:
Sébastien Guérif, Long H. Ngo, Thuong Le-Tien, Emmanuel Viennet, Marie Luong, Nikolay Metodiev Sirakov
Publikováno v:
ICIP
Web of Science
Web of Science
This paper improves the conventional sparse representation based classification (SRC) method, through incorporating wavelet coefficients. For this reason, the proposed method is called Sparse Representation Wavelet based Classification (SRWC). In the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05f41ef930a1bb37e70c80157cd9c8bd
https://doi.org/10.1109/icip.2018.8451538
https://doi.org/10.1109/icip.2018.8451538
Publikováno v:
EUSIPCO
Patch-based image denoising can be interpreted under the Bayesian framework which incorporates the image formation model and a prior image distribution. In the sparsity approach, the prior is often assumed to obey an arbitrarily chosen distribution.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bcc64645afe6347b6f4f31ca9f60580e