Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Mohammed El Amin Larabi"'
Publikováno v:
Engineering Proceedings, Vol 56, Iss 1, p 304 (2023)
Band selection is a frequently used dimension reduction technique for hyperspectral images (HSI) to address the “curse of dimensionality” phenomenon in machine learning (ML). This technique identifies and selects a subset of the most important ba
Externí odkaz:
https://doaj.org/article/8e8dce6e8fb942d2a4702728afa97eb9
Autor:
Maria Rouba, Mohammed El Amin Larabi
Publikováno v:
Engineering Proceedings, Vol 56, Iss 1, p 316 (2023)
Deep learning (DL) has become increasingly popular in recent years, with researchers and businesses alike successfully applying it to a wide range of tasks. However, one challenge that DL faces in certain domains, such as remote sensing (RS), is the
Externí odkaz:
https://doaj.org/article/2985deeb65a34070bb0d3d7c4a45e774
Publikováno v:
GeoJournal.
Autor:
Walid Rabehi, Otmani Housseyn, Mohamed Amine Bouhlala, Sarah Kreri, Oussama Benabbou, Mohammed El Amin Larabi, Hadjer Dellani
Publikováno v:
European Spatial Data for Coastal and Marine Remote Sensing ISBN: 9783031162121
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d21a3dcc79bcc4ac2e31de680d079d9
https://doi.org/10.1007/978-3-031-16213-8_9
https://doi.org/10.1007/978-3-031-16213-8_9
Publikováno v:
2022 4th International Conference on Pattern Analysis and Intelligent Systems (PAIS).
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Publikováno v:
2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS).
Publikováno v:
2022 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS).
Publikováno v:
Anuário do Instituto de Geociências; Vol 44 (2021)
Anuário do Instituto de Geociências
Universidade Federal do Rio de Janeiro (UFRJ)
instacron:UFRJ
Anuário do Instituto de Geociências
Universidade Federal do Rio de Janeiro (UFRJ)
instacron:UFRJ
Synthetic Aperture Radar (SAR) satellite imagery is a source of data widely employed in the quantification and analysis of an earthquake coseismic displacement. However, due to the signal path along the atmosphere and to other sources, the interferom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e0499a5e100f6b80e9ff4e4a9b1edf3
https://revistas.ufrj.br/index.php/aigeo/article/view/38730
https://revistas.ufrj.br/index.php/aigeo/article/view/38730