A Mesopic Lighting Evaluation Model Based on 1D Convolutional Neural Networks
| Autor: | Yennun Huang, Hung-Chung Li, Pei-Li Sun |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Mesopic vision
business.industry media_common.quotation_subject 020206 networking & telecommunications Pattern recognition 02 engineering and technology Luminance Convolutional neural network Gamut 0202 electrical engineering electronic engineering information engineering Contrast (vision) 020201 artificial intelligence & image processing Artificial intelligence business Mathematics media_common |
| Zdroj: | ICCE-TW |
| DOI: | 10.1109/icce-taiwan49838.2020.9258158 |
| Popis: | In the study, a mesopic lighting evaluation model that can be used to predict S/P ratio, mesopic luminance and color gamut volume of a white LED spectrum is proposed. The result shows that the one-dimensional convolutional neural network describes all of the indices well especially for mesopic luminance and color gamut volumes with a high coefficient of determination. In contrast, the performance of the S/P ratio is slightly unfavorable. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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