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68‐4: Speedy and Quantitative Evaluation of Luminance Non‐Uniformity Based on Deep Neural Networks.

Authors :
Tsutsukawa, Kazuki
Tabata, Nobunari
Bamba, Yusuke
Source :
SID Symposium Digest of Technical Papers; Jun2019, Vol. 50 Issue 1, p969-972, 4p
Publication Year :
2019

Abstract

We developed a method for automated evaluation of display luminance non‐uniformity using an auto‐encoder. Usually, a reconstruction loss of auto‐encoder is used for abnormality detection. In our method, we used reconstruction loss as the main indicator and cosine similarity as a secondary indicator. Our method succeeded in the non‐uniformity evaluation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0097966X
Volume :
50
Issue :
1
Database :
Complementary Index
Journal :
SID Symposium Digest of Technical Papers
Publication Type :
Academic Journal
Accession number :
136710470
Full Text :
https://doi.org/10.1002/sdtp.13087