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| Presentation | 2022-03-10 11:20 Automatic flood estimation using aerial images by CNN Soichiro Yanagihara, Tomoki Honma, Yuukou Horita (Univ.of Toyama)  IMQ2021-40 IE2021-102 MVE2021-69 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | When a wide-area disaster occurs, from the viewpoint of initial response, it is becoming more important to quickly grasp the damaged area. So, in this report, for investigating the possibility of determining the presence or absence of a disaster using machine learning, as a preliminary step, we focus on the "floods" that have occurred frequently in Japan in recent years. We use data for learning using flood images and non-flood images extracted from the LADI (Low Altitude Disaster Imagery) dataset, create a classifier for determining the presence or absence of flood occurrence using CNN (Convolutional Neural Network), and its accuracy was verified. In addition, we also analyze the features of the images classified using Grad-CAM (Gradient-weighted Class Activation Mapping). | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | LADI / CNN / Grad-CAM / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 420, IMQ2021-40, pp. 159-162, March 2022. | |
| Paper # | IMQ2021-40 | |
| Date of Issue | 2022-03-02 (IMQ, IE, MVE) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | IMQ2021-40 IE2021-102 MVE2021-69 |
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| Conference Information | |
| Committee | CQ IMQ MVE IE |
| Conference Date | 2022-03-09 - 2022-03-11 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online (Zoom) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Media of five senses, Multimedia, Media experience, Picture codinge, Image media quality, Network,quality and reliability, etc |
| Paper Information | |
| Registration To | IMQ |
| Conference Code | 2022-03-CQ-IMQ-MVE-IE |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Automatic flood estimation using aerial images by CNN |
| Sub Title (in English) | |
| Keyword(1) | LADI |
| Keyword(2) | CNN |
| Keyword(3) | Grad-CAM |
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| 1st Author's Name | Soichiro Yanagihara |
| 1st Author's Affiliation | University of Toyama (Univ.of Toyama) |
| 2nd Author's Name | Tomoki Honma |
| 2nd Author's Affiliation | University of Toyama (Univ.of Toyama) |
| 3rd Author's Name | Yuukou Horita |
| 3rd Author's Affiliation | University of Toyama (Univ.of Toyama) |
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| Speaker | Author-1 |
| Date Time | 2022-03-10 11:20:00 |
| Presentation Time | 25 minutes |
| Registration for | IMQ |
| Paper # | IMQ2021-40, IE2021-102, MVE2021-69 |
| Volume (vol) | vol.121 |
| Number (no) | no.420(IMQ), no.422(IE), no.423(MVE) |
| Page | pp.159-162 |
| #Pages | 4 |
| Date of Issue | 2022-03-02 (IMQ, IE, MVE) |
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