CESA-MCFormer: An Efficient Transformer Network for Hyperspectral Image Classification by Eliminating Redundant Information.

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Bibliographic Details
Title: CESA-MCFormer: An Efficient Transformer Network for Hyperspectral Image Classification by Eliminating Redundant Information.
Authors: Liu S; School of Software, Tongji University, Shanghai 201800, China., Yin C; School of Software, Tongji University, Shanghai 201800, China., Zhang H; School of Software, Tongji University, Shanghai 201800, China.
Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2024 Feb 11; Vol. 24 (4). Date of Electronic Publication: 2024 Feb 11.
Publication Type: Journal Article
Journal Info: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220 (Electronic) Linking ISSN: 14248220 NLM ISO Abbreviation: Sensors (Basel) Subsets: MEDLINE; PubMed not MEDLINE
Database: MEDLINE Ultimate
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ISSN:1424-8220
DOI:10.3390/s24041187