Physics-Constrained Deep Learning for Security Ink Colorimetry with Attention-Based Spectral Sensing

Physics-Constrained Deep Learning for Security Ink Colorimetry with Attention-Based Spectral Sensing

The proliferation of sophisticated counterfeiting poses critical challenges to global security and commerce, with annual losses exceeding $2.2 trillion. This paper presents a novel physics-constrained deep learning framework for high-precision security ink colorimetry, integrating three key innovati...

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Bibliographic Details
Main Authors: Po-Tong Wang, Chiu Wang Tseng, Li-Der Fang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
physics-constrained deep learning
attention-based modeling
spectral color sensing
security ink colorimetry
Bayesian optimization
anti-counterfeiting systems
Online Access:https://www.mdpi.com/1424-8220/25/1/128
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