On the analysis of adapting deep learning methods to hyperspectral imaging. Use case for WEEE recycling and dataset.
- DOI
- 10.1016/j.saa.2024.125665
- Published
- 2025 Apr 5
- Container
- Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.saa.2024.125665,
title = {On the analysis of adapting deep learning methods to hyperspectral imaging. Use case for WEEE recycling and dataset.},
author = {Picon A and Galan P and Bereciartua-Perez A and Benito-Del-Valle L},
year = {2025},
journal = {Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy},
doi = {10.1016/j.saa.2024.125665},
url = {https://doi.org/10.1016/j.saa.2024.125665}
}RIS
TY - JOUR TI - On the analysis of adapting deep learning methods to hyperspectral imaging. Use case for WEEE recycling and dataset. AU - Picon A AU - Galan P AU - Bereciartua-Perez A AU - Benito-Del-Valle L PY - 2025 JO - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy DO - 10.1016/j.saa.2024.125665 UR - https://doi.org/10.1016/j.saa.2024.125665 ER -
APA
A, P., P, G., A, B., & L, B. (2025). On the analysis of adapting deep learning methods to hyperspectral imaging. Use case for WEEE recycling and dataset.. Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy. https://doi.org/10.1016/j.saa.2024.125665
Source records
- pubmed · retrieved 2026-09-25T07:48:17.127Z