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arXiv Machine Learning By Mitsunobu Kanebako, Ami S. Koshikawa, Masaru Hitomi, Takuro Tanaka, Mahito Chiba, Maiko Mori, Masayuki Ohzeki

Robust Wavelength Selection for Partial Least Squares Sugar Content Estimation Using Combinatorial Bayesian Optimization

Read the original on arXiv Machine Learning →

arXiv:2607. 27645v1 Announce Type: cross Abstract: Wavelength selection is one of the important preprocessing methods in near-infrared spectroscopy to improve prediction accuracy and interpretability of spectral data.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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