SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

Literals

dcterms:contributor
- Hong D., Han Z., Yao J., Gao L., Zhang B., Plaza A., Chanussot J.
dcterms:publisher
- IEEE Transactions on Geoscience and Remote Sensing
bibo:issn
- 0196-2892
ou:eid
- 2-s2.0-85120553741
vivo:identifier
- 2022-979
bibo:doi
- 10.1109/tgrs.2021.3130716
ou:bibtex
- @article{Hong_2022, doi = {10.1109/tgrs.2021.3130716}, url = {https://doi.org/10.1109%2Ftgrs.2021.3130716}, year = 2022, publisher = {Institute of Electrical and Electronics Engineers ({IEEE})}, volume = {60}, pages = {1--15}, author = {Danfeng Hong and Zhu Han and Jing Yao and Lianru Gao and Bing Zhang and Antonio Plaza and Jocelyn Chanussot}, title = {{SpectralFormer}: Rethinking Hyperspectral Image Classification With Transformers}, journal = {{IEEE} Transactions on Geoscience and Remote Sensing} }
bibo:eissn
- 1558-0644
fabio:hasPublicationYear
- 2022
dcterms:creator
- Hong D.
ou:tipoPublicacion
- Article
dcterms:title
- SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers
vcard:url
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85120553741&origin=inward
ou:urlOrcid
- https://doi.org/10.1109/TGRS.2021.3130716
ou:urlScopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85120553741&origin=inward
bibo:volume
- 60