文献
J-GLOBAL ID:202202257842419868
整理番号:22A0438530
地質材料のスペクトル非混合のための深層学習ベース潜在空間符号化【JST・京大機械翻訳】
Deep-learning-based latent space encoding for spectral unmixing of geological materials
著者 (4件):
Pattathal V. Arun
(The Remote Sensing Laboratory, French Associates Institute for Agriculture and Biotechnology of Drylands, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, 8499000, Israel)
,
Sahoo Maitreya Mohan
(Centre of Studies in Resources Engineering, Indian Institute of Technology, Bombay, Mumbai 400076, India)
,
Porwal Alok
(Centre of Studies in Resources Engineering, Indian Institute of Technology, Bombay, Mumbai 400076, India)
,
Karnieli Arnon
(The Remote Sensing Laboratory, French Associates Institute for Agriculture and Biotechnology of Drylands, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, 8499000, Israel)
資料名:
ISPRS Journal of Photogrammetry and Remote Sensing (International Society for Photogrammetry and Remote Sensing)
(ISPRS Journal of Photogrammetry and Remote Sensing (International Society for Photogrammetry and Remote Sensing))
巻:
183
ページ:
307-320
発行年:
2022年
JST資料番号:
H0048A
ISSN:
0924-2716
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)