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Updated: May 30, 2025

High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
Published on: January 21, 2015
Qualitative identification of passive Fourier transform infrared spectra via an attention mechanism based deep
Abstract:
Passive Fourier transform infrared spectroscopy, used to detect chemical pollutants in the air, works with extremely weak signals with complex and varying background interference. This significantly challenges gas identification in terms of precision. Consequently, limited research progress has been made in this area. To address this issue, this study proposes a model that leverages the Transformer, a self-attention-based neural network, and a coattention mechanism for gas identification. The architecture of this model facilitates joint feature learning and fusion, rendering the prediction performance robust to background interference. Extensive experiments demonstrate its significant improvements and feasibility, underlining the potential application in hazardous gas warning systems.
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