SIMNet: An Unsupervised Framework for Accurate Gas Species Quantification Under Unknown Interference

We present SIMNet, an unsupervised framework for mitigating spectral inter-ference in gas detection. Using a single cw-ICL and tailored augmentations, SIMNet enables accurate C1–C3 hydrocarbon quantification despite unknown interferents.

Authors

Mohammed Sait (ORCID: https://orcid.org/0000-0002-7861-290X)
Aamir Farooq (ORCID: https://orcid.org/0000-0001-5296-2197)
Mohamed Sy (ORCID: https://orcid.org/0000-0002-9411-5321)
Shams Musheer

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.1364/cleo_at.2025.jps100_5
Primary Topic: Spectroscopy and Laser Applications
Type: article
Field-Weighted Citation Impact: 0.00

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article

SIMNet: An Unsupervised Framework for Accurate Gas Species Quantification Under Unknown Interference

Mohammed Sait, Aamir Farooq, Mohamed Sy, Shams Musheer

Jan 1, 2025

Spectroscopy and Laser Applications

article

SIMNet: An Unsupervised Framework for Accurate Gas Species Quantification Under Unknown Interference

Mohammed Sait, Aamir Farooq, Mohamed Sy, Shams Musheer

January 1, 2025article en

Abstract

Openalex Percentile: Top 76%

Spectroscopy and Laser Applications

DOI Source OpenAlex

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SIMNet: An Unsupervised Framework for Accurate Gas Species Quantification Under Unknown Interference — Mohammed Sait, Aamir Farooq, et al. · (2025) | TGRS Research Map | TGRS