Inproceedings,
Deep Attention-Driven HSI Scene Classification Based on Inverted Dot-Product.
M. Paoletti, X. Tao, L. Han, Z. Wu, S. Moreno-Álvarez, and J. Haut.IGARSS, page 1380-1383. IEEE, (2022)
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- BibTeX key
- conf/igarss/PaolettiTHWMH22
- entry type
- inproceedings
- booktitle
- IGARSS
- year
- 2022
- pages
- 1380-1383
- publisher
- IEEE
- crossref
- conf/igarss/2022
- ee
- https://doi.org/10.1109/IGARSS46834.2022.9883028
- isbn
- 978-1-6654-2792-0
- url
- http://dblp.uni-trier.de/db/conf/igarss/igarss2022.html#PaolettiTHWMH22
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%1 conf/igarss/PaolettiTHWMH22
%A Paoletti, Mercedes Eugenia
%A Tao, Xuanwen
%A Han, Lirong
%A Wu, Zhaoyue
%A Moreno-Álvarez, Sergio
%A Haut, Juan Mario
%B IGARSS
%D 2022
%I IEEE
%K dblp
%P 1380-1383
%T Deep Attention-Driven HSI Scene Classification Based on Inverted Dot-Product.
%U http://dblp.uni-trier.de/db/conf/igarss/igarss2022.html#PaolettiTHWMH22
%@ 978-1-6654-2792-0
@inproceedings{conf/igarss/PaolettiTHWMH22,
added-at = {2024-02-05T00:00:00.000+0100},
author = {Paoletti, Mercedes Eugenia and Tao, Xuanwen and Han, Lirong and Wu, Zhaoyue and Moreno-Álvarez, Sergio and Haut, Juan Mario},
biburl = {https://www.bibsonomy.org/bibtex/2320b9a19fb8ed1bc73cdec24782c0b49/dblp},
booktitle = {IGARSS},
crossref = {conf/igarss/2022},
ee = {https://doi.org/10.1109/IGARSS46834.2022.9883028},
interhash = {b18e3e4f794ed7775ffef413eaa734ca},
intrahash = {320b9a19fb8ed1bc73cdec24782c0b49},
isbn = {978-1-6654-2792-0},
keywords = {dblp},
pages = {1380-1383},
publisher = {IEEE},
timestamp = {2024-04-10T01:11:01.000+0200},
title = {Deep Attention-Driven HSI Scene Classification Based on Inverted Dot-Product.},
url = {http://dblp.uni-trier.de/db/conf/igarss/igarss2022.html#PaolettiTHWMH22},
year = 2022
}