Perceptual Color Appearance Models of Fluorescent Samples Based on Machine Learning

Autor:	Hung-Shing Chen, Wei-Chih Su, Pei-Li Sun, Hung-Chung Li, Yennun Huang, Chia-Pin Chueh
Rok vydání:	2020
Předmět:	Visual perception Artificial neural network Mean squared error business.industry Computer science media_common.quotation_subject Machine learning computer.software_genre Fluorescence Visualization Perception Artificial intelligence business computer Polynomial regression model media_common
Zdroj:	2020 Opto-Electronics and Communications Conference (OECC).
DOI:	10.1109/oecc48412.2020.9273718
Popis:	Two machine learning models, including the polynomial regression model and artificial neural network, are proposed based on the result of a visual perception experiment of fluorescent samples. The results indicate that both two models can ideally predict the visual color appearance of fluorescent samples under various lighting conditions with high R-squared, acceptable RMSE, and MAE values.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::29dba3c7ec8c6c7e72175664e77c333c https://doi.org/10.1109/oecc48412.2020.9273718 Zobrazit plný text záznamu