RUS  ENG
Full version
JOURNALS // Mendeleev Communications // Archive
Mendeleev Commun., 2024 Volume 34, Issue 6, Pages 786–787 (Mi mendc251)
Communications

Contrastive representation learning for spectroscopy data analysis

A. P. Vorozhtsov, P. V. Kitina

Department of Fundamental Physical and Chemical Engineering, M.V. Lomonosov Moscow State University, Moscow, Russian Federation

Abstract: Metric-based representation learning showed good accuracy in identifying objects from one-dimensional spectroscopy data, robustness to small dataset size and the ability to change the data domain without fine-tuning.

Keywords: spectroscopy, machine learning, representation learning, neural network, metric learning, spectra analysis.

Language: English

DOI: 10.1016/j.mencom.2024.10.006



Bibliographic databases:

© Steklov Math. Inst. of RAS, 2025