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J-GLOBAL ID：202402237601376682   Reference number：24A0213674

Tri-CNN: A Three Branch Model for Hyperspectral Image Classification

Tri-CNN:ハイパースペクトル画像分類のための3分岐モデル【JST・京大機械翻訳】

Author (8)： Alkhatib Mohammed Q. (Collage of Engineering and IT, University of Dubai, Dubai P.O. Box 14143, United Arab Emirates) ,  Al-Saad Mina (Collage of Engineering and IT, University of Dubai, Dubai P.O. Box 14143, United Arab Emirates) ,  Aburaed Nour (Collage of Engineering and IT, University of Dubai, Dubai P.O. Box 14143, United Arab Emirates) ,  Aburaed Nour (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK) ,  Almansoori Saeed (Mohammed Bin Rashid Space Center, Dubai P.O. Box 211833, United Arab Emirates) ,  Zabalza Jaime (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK) ,  Marshall Stephen (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK) ,  Al-Ahmad Hussain (Collage of Engineering and IT, University of Dubai, Dubai P.O. Box 14143, United Arab Emirates)
Material： Remote Sensing (Web)
Volume： 15  Issue： 2  Page： 316  Publication year： 2023 
JST Material Number： U7270A  ISSN： 2072-4292  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Hyperspectral Image (HSI) clas...

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Thesaurus term： learning ,  *classification ,  characteristic ,  neural network(biomodel) ,  feature extraction ,  *spectrum ,  two dimension ,  three dimension ,  machine learning
Semi thesaurus term： 地理空間情報 ,  *ハイパースペクトル ,  *ハイパースペクトル画像 ,  マルチスケール ,  特徴融合 ,  深層学習 ,  *ハイパースペクトル画像分類 ,  畳込みニューラルネットワーク , 【Automatic Indexing@JST】

Author keywords (4)： hyperspectral classification ,  Convolutional Neural Networks ,  deep learning ,  feature fusion

JST classification (2)： Pattern recognition  (JE07000S) ,  Artificial intelligence  (JE08000Z)

Reference (55)：

• Moroni, M.; Lupo, E.; Marra, E.; Cenedese, A. Hyperspectral image analysis in environmental monitoring: Setup of a new tunable filter platform. Procedia Environ. Sci. 2013, 19, 885-894.
• Stuart, M.B.; McGonigle, A.J.; Willmott, J.R. Hyperspectral imaging in environmental monitoring: A review of recent developments and technological advances in compact field deployable systems. Sensors 2019, 19, 3071.
• Ad ao, T.; Hruška, J.; Pádua, L.; Bessa, J.; Peres, E.; Morais, R.; Sousa, J.J. Hyperspectral imaging: A review on UAV-based sensors, data processing and applications for agriculture and forestry. Remote Sens. 2017, 9, 1110.
• Dale, L.M.; Thewis, A.; Boudry, C.; Rotar, I.; Dardenne, P.; Baeten, V.; Pierna, J.A.F. Hyperspectral imaging applications in agriculture and agro-food product quality and safety control: A review. Appl. Spectrosc. Rev. 2013, 48, 142-159.
• Park, B.; Lu, R. Hyperspectral Imaging Technology in Food and Agriculture; Springer: Berlin/Heidelberg, Germany, 2015.

Terms in the title (5)： TRI ,  CNN ,  ハイパースペクトル画像分類 ,  分岐 ,  モデル