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| Presentation | 2021-03-04 14:10 Hardware Implementation of Object Recognition Neural Network using Depth Images Yuma Yoshimoto (Kyutech/JSPS Research Fellow), Hakaru Tamukoh (Kyutech/Research Center for Neuromorphic AI Hardware)  SIS2020-47 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this study, we propose an object recognition neural network using depth images, implemented on an FPGA for service robots. The proposed method achieves 4.7 points higher accuracy than Binarized VGG-16, which is one of the hardware-oriented convolutional neural networks. The network implemented on the FPGA is about 4.7 times faster than the network implemented on a CPU and about 1.9 times faster than the network implemented on a GPU. Also, the network is about 20 times more power-efficient than the network implemented on a CPU and about 8 times more power-efficient than the network implemented on a GPU. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Object Recognition / FPGA / CNN / Depth Images / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 415, SIS2020-47, pp. 67-70, March 2021. | |
| Paper # | SIS2020-47 | |
| Date of Issue | 2021-02-25 (SIS) | |
| 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 | SIS2020-47 |
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| Conference Information | |
| Committee | SIS |
| Conference Date | 2021-03-04 - 2021-03-05 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Soft Computing, etc. |
| Paper Information | |
| Registration To | SIS |
| Conference Code | 2021-03-SIS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Hardware Implementation of Object Recognition Neural Network using Depth Images |
| Sub Title (in English) | |
| Keyword(1) | Object Recognition |
| Keyword(2) | FPGA |
| Keyword(3) | CNN |
| Keyword(4) | Depth Images |
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| 1st Author's Name | Yuma Yoshimoto |
| 1st Author's Affiliation | Kyushu Institute of Technology/Research Fellow of Japan Society for the Promotion of Science (Kyutech/JSPS Research Fellow) |
| 2nd Author's Name | Hakaru Tamukoh |
| 2nd Author's Affiliation | Kyushu Institute of Technology/Research Center for Neuromorphic AI Hardware (Kyutech/Research Center for Neuromorphic AI Hardware) |
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| Speaker | Author-1 |
| Date Time | 2021-03-04 14:10:00 |
| Presentation Time | 20 minutes |
| Registration for | SIS |
| Paper # | SIS2020-47 |
| Volume (vol) | vol.120 |
| Number (no) | no.415 |
| Page | pp.67-70 |
| #Pages | 4 |
| Date of Issue | 2021-02-25 (SIS) |
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