Spectral–Spatial Morphological Attention Transformer for Hyperspectral Image Classification-Reference-Cited by-同舟云学术

Spectral–Spatial Morphological Attention Transformer for Hyperspectral Image Classification

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Roy Swalpa Kumar¹^ORCID,Deria Ankur²^ORCID,Shah Chiranjibi³^ORCID,Haut Juan M.⁴^ORCID,Du Qian³^ORCID,Plaza Antonio⁴^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Jalpaiguri Government Engineering College, Jalpaiguri, India

2. Department of Informatics, Technical University of Munich, Garching bei München, Germany

3. Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA

4. Department of Technology of Computers and Communications, Hyperspectral Computing Laboratory, Escuela Politécnica, University of Extremadura, Cáceres, Spain

Funder

Consejeria de Economia, Ciencia y Agencia Digital de la Junta de Extremadura, and Fondo Europeo de Desarrollo Regional de la Union Europea

Spanish Ministerio de Ciencia e Innovacion

European Union’s Horizon 2020 Research and Innovation Program

Science and Engineering Research Board (SERB), Government of India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10036472.pdf?arnumber=10036472

Reference72 articles.

1. Local morphological pattern: A scale space shape descriptor for texture classification

2. ORSIm Detector: A Novel Object Detection Framework in Optical Remote Sensing Imagery Using Spatial-Frequency Channel Features

3. A new approach for the morphological segmentation of high-resolution satellite imagery

4. Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning

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