教員業績データベース |
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言語種別 | 英語 |
演題 | A Preliminary Study on Automatic Recognition of Bedside Monitor Output Enhanced by
YOLO with Fisheye Camera |
学会名 | IEEE EMBC 2023 |
主催者 | IEEE |
学会区分 | 国際学会 |
発表形態 | ポスター掲示 |
発表形式 | 一般 |
発表形式名 | 一般 |
発表者・共同発表者 | Rumi Iwai, Takunori Shimazaki, Yoshifumi Kawakubo, Jun Mitsudo, Yuhei Hayashi, Shingo Ata, Takeshi Yokoyama,Daisuke Anzai |
発表年月日 | 2023/07/26 |
国名 | オーストラリア |
開催地 (都市, 国名) |
Sydney |
開催期間 | 2023/07/24~2023/07/27 |
概要 | This study investigated the effectiveness of automatic recognition on bedside monitor
output by combining a fisheye camera and you only look once (YOLO), which is one of the real-time object detection algorithms, as a preliminary study. First, with a fisheye camera placed above the monitor, the developed system adjusted the distortion of the acquired image file. Then, the YOLO algorithm was applied to recognize the monitor output, including waveforms and numbers on the axes. The evaluation result was obtained as mAP (mean average precision) = 0.84, which clearly demonstrated the effectiveness of the image quantification of the bedside monitor for supporting remote area medicine. |