@inproceedings{e202d6f5e1504ba89df25fe2f2a6d5c0,
title = "Material Classification Based on Multi-Spectral NIR Band Image",
abstract = "In this paper, we study the usefulness of multi-spectral NIR band images instead of RGB only for material classification. To effectively learn a target material, the proposed method uses multi-spectral NIR bands which provide more information than a single NIR band. A new NIR multi-band dataset was built using the hyperspectral camera. As a result, we can find a meaningful correlation with NIR multi bands, and effectively classify the surface material of an object.",
keywords = "material classification, Multi-spectral band, near-infrared (NIR), surface material",
author = "Han, {Dong Keun} and Ha, {Jeong Won} and Kim, {Jong Ok}",
note = "Funding Information: This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2020R1A4A4079705) and in part by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2020-0-01749) supervised by the IITP(Institute of Information & Communications Technology Planning & Evaluation). Publisher Copyright: {\textcopyright} 2022 IEEE.; 37th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2022 ; Conference date: 05-07-2022 Through 08-07-2022",
year = "2022",
doi = "10.1109/ITC-CSCC55581.2022.9894969",
language = "English",
series = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "940--942",
booktitle = "ITC-CSCC 2022 - 37th International Technical Conference on Circuits/Systems, Computers and Communications",
}