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| Presentation | 2023-05-19 10:20 Evaluation of Multi-edge Object Detection System using Deep Feature Compression Transmission Kohji Yamada, Yuichiro Kora, Meguru Yamazaki, Xuying Lei (Fujitsu)  SeMI2023-13 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Collaborative Intelligence has been proposed to divide DNN model and perform inferences collaborating on edge and cloud. Deep feature compression transmission has been developed to extract deep feature by executing the first half of the DNN model at the edge and compress the deep feature by Autoencoder and transmit the compressed deep feature to cloud and restore the compressed deep feature and execute the second half of the DNN model. It has been confirmed that the deep feature compression transmission technology can perform inference with low delay in a one-to-one configuration between an edge device and a server. In this paper, we report the performance evaluation of a deep feature compression transmission system, such as a video monitoring system, in which multiple edge devices are connected to a single server. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Deep Feature Compression Transmission / Deep Learning / Low Latency, / Collaborative Intelligence / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 31, SeMI2023-13, pp. 53-57, May 2023. | |
| Paper # | SeMI2023-13 | |
| Date of Issue | 2023-05-11 (SeMI) | |
| 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 | SeMI2023-13 |
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| Conference Information | |
| Committee | SeMI IPSJ-ITS IPSJ-MBL IPSJ-DPS |
| Conference Date | 2023-05-18 - 2023-05-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Institute of Science and Technology (OIST) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SeMI |
| Conference Code | 2023-05-SeMI-ITS-MBL-DPS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluation of Multi-edge Object Detection System using Deep Feature Compression Transmission |
| Sub Title (in English) | |
| Keyword(1) | Deep Feature Compression Transmission |
| Keyword(2) | Deep Learning |
| Keyword(3) | Low Latency, |
| Keyword(4) | Collaborative Intelligence |
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| Keyword(8) | |
| 1st Author's Name | Kohji Yamada |
| 1st Author's Affiliation | Fujitsu Limited (Fujitsu) |
| 2nd Author's Name | Yuichiro Kora |
| 2nd Author's Affiliation | Fujitsu Limited (Fujitsu) |
| 3rd Author's Name | Meguru Yamazaki |
| 3rd Author's Affiliation | Fujitsu Limited (Fujitsu) |
| 4th Author's Name | Xuying Lei |
| 4th Author's Affiliation | Fujitsu Limited (Fujitsu) |
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| Speaker | Author-1 |
| Date Time | 2023-05-19 10:20:00 |
| Presentation Time | 15 minutes |
| Registration for | SeMI |
| Paper # | SeMI2023-13 |
| Volume (vol) | vol.123 |
| Number (no) | no.31 |
| Page | pp.53-57 |
| #Pages | 5 |
| Date of Issue | 2023-05-11 (SeMI) |
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