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| Paper Abstract and Keywords | ||
| Presentation | 2018-05-17 14:30 Prediction Method by Deep-Learning using Convolutional Neural Network for Path Loss Characteristics in An Open-Square Environment Nobuaki Kuno, Motoharu Sasaki, Yasushi Takatori (NTT)  AP2018-21 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | By using convolutional neural network which is widely used for recent image recognition etc., we propose a path loss prediction method in an open-square environment. By using ray-tracing data for learning, we verified whether the model can consider the influence of multiple blockages. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Deep-Learning / Convolutional Neural Network / Machine-Learning / Path Loss / Open-Square Environment / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 37, AP2018-21, pp. 47-51, May 2018. | |
| Paper # | AP2018-21 | |
| Date of Issue | 2018-05-10 (AP) | |
| 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 | AP2018-21 |
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| Conference Information | |
| Committee | AP |
| Conference Date | 2018-05-17 - 2018-05-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kumamoto Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Radio propagation, Antennas and Propagation |
| Paper Information | |
| Registration To | AP |
| Conference Code | 2018-05-AP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Prediction Method by Deep-Learning using Convolutional Neural Network for Path Loss Characteristics in An Open-Square Environment |
| Sub Title (in English) | |
| Keyword(1) | Deep-Learning |
| Keyword(2) | Convolutional Neural Network |
| Keyword(3) | Machine-Learning |
| Keyword(4) | Path Loss |
| Keyword(5) | Open-Square Environment |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Nobuaki Kuno |
| 1st Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 2nd Author's Name | Motoharu Sasaki |
| 2nd Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
| 3rd Author's Name | Yasushi Takatori |
| 3rd Author's Affiliation | Nippon Telegraph and Telephone Corporation (NTT) |
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| Speaker | Author-1 |
| Date Time | 2018-05-17 14:30:00 |
| Presentation Time | 25 minutes |
| Registration for | AP |
| Paper # | AP2018-21 |
| Volume (vol) | vol.118 |
| Number (no) | no.37 |
| Page | pp.47-51 |
| #Pages | 5 |
| Date of Issue | 2018-05-10 (AP) |
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