@inproceedings{a552d143288e440482878fb05b7665b9,
title = "Visible and near-infrared separation using conditional generative adversarial network",
abstract = "Visible and near-infrared image acquisition using a single conventional image sensor helps simpler implementation on mobile devices. This paper presents a signal separation method of visible and near-infrared images from an image which has mixed visible and near-infrared signals captured by a single CMOS sensor. In the separation process, the conditional generative adversarial network is applied to extract each visible and near-infrared image from the mixed one. For the experiment, a conventional digital camera is used with a simple modification. The experimental result shows that the proposed method well extracts both visible and near-infrared images.",
keywords = "generative adversarial network, machine learning, near-infrared, NIR",
author = "Younghyeon Park and Byeungwoo Jeon",
note = "Publisher Copyright: {\textcopyright} 2018 Institute of Electronics and Information Engineers.; 17th International Conference on Electronics, Information and Communication, ICEIC 2018 ; Conference date: 24-01-2018 Through 27-01-2018",
year = "2018",
month = apr,
day = "2",
doi = "10.23919/ELINFOCOM.2018.8330670",
language = "English",
series = "International Conference on Electronics, Information and Communication, ICEIC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--2",
booktitle = "International Conference on Electronics, Information and Communication, ICEIC 2018",
}