Attention-based multiscale deep learning with unsampled pixel utilization for hyperspectral image classification-Reference-Cited by-同舟云学术

Attention-based multiscale deep learning with unsampled pixel utilization for hyperspectral image classification

Published:2023-07-25 Issue:1 Volume:38 Page:
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

AL-Kubaisi Mohammed Ahmed¹²,Shafri Helmi Z. M.¹³,Ismail Mohd Hasmadi⁴,Yusof Mohd Johari Mohd⁵,Jahari bin Hashim Shaiful⁶

Affiliation:

1. Department of Civil Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia

2. Directorate of Anbar Environment, Ministry of Environment, Anbar, Iraq

3. Geospatial Information Science Research Centre (GISRC), Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, Selangor, Malaysia

4. Department of Forestry Science and Biodiversity, Faculty of Forestry, Universiti Putra Malaysia, Serdang, Selangor Darul Ehsan, Malaysia

5. Faculty of Design and Architecture, University Putra Malaysia, Serdang, Selangor, Malaysia

6. Department of Computer and Communication Systems Engineering, University Putra Malaysia, Selangor, Malaysia

Funder

Universiti Putra Malaysia;Iraqi Ministry of Environment, Al-Anbar Environment Directorate

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2023.2231428

Reference72 articles.

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5. Caballero D, Calvini R, Amigo JM. 2019. Hyperspectral imaging in crop fields: precision agriculture. In Data handling in science and technology.Vol. 32. Amsterdam, The Netherlands: Elsevier. p. 453–473.

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