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Reevaluating Convolutional Neural Networks for Spectral Analysis: A Focus on Raman Spectroscopy

Published in ACS Earth and Space Chemistry, 2025

This study revisits how convolutional neural networks handle Raman spectra, showing that their performance depends strongly on pooling, training strategy, and dataset size—factors that are critical for autonomous spectroscopic instruments in planetary and ocean exploration.

Recommended citation: Deniz Soysal, Xabier Garcia-Andrade, Laura E. Rodriguez, Pablo Sobron, Laura M. Barge, Renaud Detry. (2025). "Reevaluating Convolutional Neural Networks for Spectral Analysis: A Focus on Raman Spectroscopy." ACS Earth and Space Chemistry. DOI: 10.1021/acsearthspacechem.5c00136.
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Undergraduate course, University 1, Department, 2014

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Workshop, University 1, Department, 2015

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