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| Presentation | 2018-07-19 15:20 GPR Image Recognition by Transfer Learning with FDTD Simulation on Deep Learning Jun Sonoda (NIT, Sendai), Tomoyuki Kimoto (NIT, Oita)  EMT2018-17 MW2018-32 OPE2018-20 EST2018-15 MWP2018-16 Link to ES Tech. Rep. Archives: EMT2018-17 MW2018-32 OPE2018-20 EST2018-15 MWP2018-16 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this study, to automatically detect underground objects from the ground penetrating radar (GPR) images by the deep neural network (DNN), we have generated GPR images for training the DNN using a fast finite-difference time-domain (FDTD) simulation with graphics processing units (GPUs). Also, we have obtained characteristics of underground objects using the generated GPR images with a convolutional neural network (CNN) and finetuning using a modified VGG16 trained by the ImageNet. It is shown that the CNN and the VGG16 can identify four materials of experimental GPR images roughly 75% and 80% accuracy, respectively. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Deep learning / transfer learning / VGG16 / CNN / ground penetrating radar / FDTD / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 144, EST2018-15, pp. 59-62, July 2018. | |
| Paper # | EST2018-15 | |
| Date of Issue | 2018-07-12 (EMT, MW, OPE, EST, MWP) | |
| ISSN | Print edition: ISSN 0913-5685 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 | EMT2018-17 MW2018-32 OPE2018-20 EST2018-15 MWP2018-16 Link to ES Tech. Rep. Archives: EMT2018-17 MW2018-32 OPE2018-20 EST2018-15 MWP2018-16 |
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| Conference Information | |
| Committee | EST MW OPE MWP EMT IEE-EMT THz |
| Conference Date | 2018-07-19 - 2018-07-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | EST |
| Conference Code | 2018-07-EST-MW-OPE-MWP-EMT-EMT-THz |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | GPR Image Recognition by Transfer Learning with FDTD Simulation on Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | Deep learning |
| Keyword(2) | transfer learning |
| Keyword(3) | VGG16 |
| Keyword(4) | CNN |
| Keyword(5) | ground penetrating radar |
| Keyword(6) | FDTD |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Jun Sonoda |
| 1st Author's Affiliation | National Institute of Technology, Sendai College (NIT, Sendai) |
| 2nd Author's Name | Tomoyuki Kimoto |
| 2nd Author's Affiliation | National Institute of Technology, Oita College (NIT, Oita) |
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| Speaker | Author-1 |
| Date Time | 2018-07-19 15:20:00 |
| Presentation Time | 25 minutes |
| Registration for | EST |
| Paper # | EMT2018-17, MW2018-32, OPE2018-20, EST2018-15, MWP2018-16 |
| Volume (vol) | vol.118 |
| Number (no) | no.141(EMT), no.142(MW), no.143(OPE), no.144(EST), no.145(MWP) |
| Page | pp.59-62 |
| #Pages | 4 |
| Date of Issue | 2018-07-12 (EMT, MW, OPE, EST, MWP) |
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