Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Jihan Alameddine"'
Publikováno v:
Remote Sensing, Vol 13, Iss 23, p 4874 (2021)
In this paper, we propose a true unsupervised method to partition large-size images, where the number of classes, training samples, and other a priori information is not known. Thus, partitioning an image without any knowledge is a great challenge. T
Externí odkaz:
https://doaj.org/article/e4677b0228c94c10b521f5ff832222ba
Publikováno v:
IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2022, Kuala Lumpur, Malaysia. ⟨10.1109/IGARSS46834.2022.9883607⟩
IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2022, Kuala Lumpur, Malaysia. ⟨10.1109/IGARSS46834.2022.9883607⟩
International audience; In this paper, we propose a new unsupervised and automatic method for the selection of training samples. Thanks to this completely unsupervised method, the samples to be used in the learning task are selected according to obje
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f13efec38fefe03c3d47b39cfe79b4a4
https://hal.science/hal-04086990
https://hal.science/hal-04086990
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cbb1cc164d64d0d07fc3dbd5ff5cd96
https://doi.org/10.2139/ssrn.4149712
https://doi.org/10.2139/ssrn.4149712
Publikováno v:
Remote Sensing, Vol 13, Iss 4874, p 4874 (2021)
Remote Sensing; Volume 13; Issue 23; Pages: 4874
Remote Sensing
Remote Sensing, 2021, 13 (23), pp.4874. ⟨10.3390/rs13234874⟩
Remote Sensing; Volume 13; Issue 23; Pages: 4874
Remote Sensing
Remote Sensing, 2021, 13 (23), pp.4874. ⟨10.3390/rs13234874⟩
International audience; In this paper, we propose a true unsupervised method to partition large-size images, where the number of classes, training samples, and other a priori information is not known. Thus, partitioning an image without any knowledge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bd820264e76388c4329ff9a803d0609
https://www.mdpi.com/2072-4292/13/23/4874
https://www.mdpi.com/2072-4292/13/23/4874
Publikováno v:
Image and Signal Processing for Remote Sensing XXV
Image and Signal Processing for Remote Sensing XXV, Sep 2019, Strasbourg, France. pp.11, ⟨10.1117/12.2533164⟩
Image and Signal Processing for Remote Sensing XXV, Sep 2019, Strasbourg, France. pp.11, ⟨10.1117/12.2533164⟩
Affinity propagation (AP) is one of the most recent unsupervised classification methods used. Its property is very interesting, but its use reveals the existence of three drawbacks which seriously hamper its usage. These concern its sensitivity to: (
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7c6f134ed63038bf7f08dfaf52b0bca
https://hal.archives-ouvertes.fr/hal-02354579
https://hal.archives-ouvertes.fr/hal-02354579