This study presents a machine-learning (ML) framework called thicknessML, which rapidly extracts film thickness from spectroscopic reflection and transmission.
This sofware package implements thicknessML framework that rapidly extracts/predicts semiconductor thin film thickness d from optical spectroscopic ...
Jun 14, 2022 · High-throughput experimentation with autonomous workflows, increasingly used to screen and optimize optoelectronic thin films, ...
Jul 13, 2023 · Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films†.
Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films.
Apr 25, 2024 · Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films. CoRR abs/2207.02209 (2022); 2020. [i2].
Correction for 'Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films' by Siyu ...
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Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films. SIP Tian, Z Ren, S ...
Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films. CoRR abs/2207.02209 (2022); 2020. [i1]. view. electronic ...
Tackling Data Scarcity with Transfer Learning: A Case Study of. Thickness Characterization from Optical Spectra of Perovskite Thin Films. Siyu Isaac Parker ...