IL-HS: a deep inception-LSTM architecture for enhanced lithological mapping using EnMAP hyperspectral remote sensing data.

Khandouch Y, Hajaj S, El Harti A, Pour AB, Laamrani A, Ouzemou JE, Flah A, Ghazouani N.

Open source

DOI: 10.1038/s41598-026-52520-9
Published: 2026-05-17
Container: Sci Rep
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1038/s41598-026-52520-9,
  title = {IL-HS: a deep inception-LSTM architecture for enhanced lithological mapping using EnMAP hyperspectral remote sensing data.},
  author = {Khandouch Y and  Hajaj S and  El Harti A and  Pour AB and  Laamrani A and  Ouzemou JE and  Flah A and  Ghazouani N.},
  year = {2026},
  journal = {Sci Rep},
  doi = {10.1038/s41598-026-52520-9},
  url = {https://doi.org/10.1038/s41598-026-52520-9}
}

RIS

TY  - JOUR
TI  - IL-HS: a deep inception-LSTM architecture for enhanced lithological mapping using EnMAP hyperspectral remote sensing data.
AU  - Khandouch Y
AU  -  Hajaj S
AU  -  El Harti A
AU  -  Pour AB
AU  -  Laamrani A
AU  -  Ouzemou JE
AU  -  Flah A
AU  -  Ghazouani N.
PY  - 2026
JO  - Sci Rep
DO  - 10.1038/s41598-026-52520-9
UR  - https://doi.org/10.1038/s41598-026-52520-9
ER  -

APA

Y, K., S, H., A, E. H., AB, P., A, L., JE, O., A, F., & N., G. (2026). IL-HS: a deep inception-LSTM architecture for enhanced lithological mapping using EnMAP hyperspectral remote sensing data.. Sci Rep. https://doi.org/10.1038/s41598-026-52520-9

Source records

europe-pmc · retrieved 2026-11-10T13:42:19.057Z
doaj · retrieved 2026-11-10T13:42:19.047Z