Unsupervised learning with a physics-based autoencoder for estimating the thickness and mixing ratio of pigments

Layered surface objects represented by decorated tomb murals and watercolors are in danger of deterioration and damage. To address these dangers, it is necessary to analyze the pigments' thickness and mixing ratio and record the current status. This paper proposes an unsupervised autoencoder mo...

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Veröffentlicht in:	Journal of the Optical Society of America. A, Optics, image science, and vision Jg. 40; H. 1; S. 116
Hauptverfasser:	Shitomi, Ryuta, Tsuji, Mayuka, Fujimura, Yuki, Funatomi, Takuya, Mukaigawa, Yasuhiro, Morimoto, Tetsuro, Oishi, Takeshi, Takamatsu, Jun, Ikeuchi, Katsushi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 01.01.2023
ISSN:	1520-8532, 1520-8532
Online-Zugang:	Weitere Angaben
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