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5 articles tagged deep learning.
A survey of 2026 papers on deep learning for Raman peak resolution: self-supervised transformers, learned baselines, simulation-driven denoising, and benchmarks that keep 1D CNNs in the game.
Recent peer-reviewed work on transfer learning in Raman and NIR classifier training reports real gains on small labelled sets, but the cross-instrument and cross-matrix picture is still uneven.
March-May 2026 in ACS Analytical Chemistry: three threads for process analytics - close-focus Raman probes for turbid streams, deep-learning chemometrics, and open-source spectroscopy tooling.
Six recent reviews map where hyperspectral imaging now sits as a process-analytics tool in pharma, food, recycling, and beyond - and where chemometrics, data hunger, and standards still hold it back.
Five recent papers sketch where deep-learning chemometrics sits versus PLS for process Raman: a public bioprocess benchmark, two classifier benchmarks, self-supervised pre-training, and an explainability tool for GMP.