@inproceedings{ea0e6413ebcc4ddfac418c4bacc2fc4d,
title = "Lighting Variability Correction for Pill Identification",
abstract = "This paper proposes a novel method for the compensation of the illumination variations. To find accurate approximate of the shading conditions, class activation map (CAM) obtained by the output of convolutional neural networks (CNNs) provides weights for the shading parameter estimation. We applied the shading compensation to the pill images, and obtained improved surface images.",
keywords = "Class activation map, Convolutional neural network, Illumination compensation, Object recognition",
author = "Seungtae Kang and Jang, {Gil Jin} and Minho Lee",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2018 ; Conference date: 24-06-2018 Through 26-06-2018",
year = "2018",
month = nov,
day = "28",
doi = "10.1109/ICCE-ASIA.2018.8552143",
language = "English",
series = "2018 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2018",
address = "United States",
}