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| Presentation | 2022-09-13 15:30 The efficient AI System for Rating Facial Expressions for the purpose of Predicting Drivers Sleepiness Tomoya Kubo (Okayama Prefectural Univ. Graduate School), Kazutami Arimoto, Tomoyuki Yokogawa, Masaki Hokari (Okayama Prefectural Univ.), Isao Kayano (Kawasaki Univ. of Medical Welfare), Kagehisa Kajiwara (MURAKAMI CORPORATION)  LOIS2022-13 IE2022-35 EMM2022-41 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In a driver monitoring system, a 3D convolutional neural network (3D CNN) has been used as a neural network (NN) to evaluate facial expressions on an AI system, but it is too computationally expensive to run on a microcontroller board that can be installed in a car. In this study, we aimed to reduce the computational complexity in the NN while maintaining accuracy by downsizing from a 3D CNN to a 2D CNN. As a result, we succeeded in increasing the processing speed by approximately 8 times while maintaining a certain degree of accuracy in inference. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Driver Monitoring System / Facial Expression Evaluation / 2D CNN / 3D CNN / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 179, EMM2022-41, pp. 19-24, Sept. 2022. | |
| Paper # | EMM2022-41 | |
| Date of Issue | 2022-09-06 (LOIS, IE, EMM) | |
| 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 | LOIS2022-13 IE2022-35 EMM2022-41 |
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| Conference Information | |
| Committee | ITE-ME EMM IE LOIS IEE-CMN IPSJ-AVM |
| Conference Date | 2022-09-13 - 2022-09-14 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Keio Univ. Yagami Campus (Hybrid) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | EMM |
| Conference Code | 2022-09-ME-EMM-IE-LOIS-CMN-AVM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | The efficient AI System for Rating Facial Expressions for the purpose of Predicting Drivers Sleepiness |
| Sub Title (in English) | |
| Keyword(1) | Driver Monitoring System |
| Keyword(2) | Facial Expression Evaluation |
| Keyword(3) | 2D CNN |
| Keyword(4) | 3D CNN |
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| 1st Author's Name | Tomoya Kubo |
| 1st Author's Affiliation | Okayama Prefectural University Graduate School (Okayama Prefectural Univ. Graduate School) |
| 2nd Author's Name | Kazutami Arimoto |
| 2nd Author's Affiliation | Okayama Prefectural University (Okayama Prefectural Univ.) |
| 3rd Author's Name | Tomoyuki Yokogawa |
| 3rd Author's Affiliation | Okayama Prefectural University (Okayama Prefectural Univ.) |
| 4th Author's Name | Masaki Hokari |
| 4th Author's Affiliation | Okayama Prefectural University (Okayama Prefectural Univ.) |
| 5th Author's Name | Isao Kayano |
| 5th Author's Affiliation | Kawasaki University of Medical Welfare (Kawasaki Univ. of Medical Welfare) |
| 6th Author's Name | Kagehisa Kajiwara |
| 6th Author's Affiliation | MURAKAMI CORPORATION (MURAKAMI CORPORATION) |
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| Speaker | Author-1 |
| Date Time | 2022-09-13 15:30:00 |
| Presentation Time | 20 minutes |
| Registration for | EMM |
| Paper # | LOIS2022-13, IE2022-35, EMM2022-41 |
| Volume (vol) | vol.122 |
| Number (no) | no.177(LOIS), no.178(IE), no.179(EMM) |
| Page | pp.19-24 |
| #Pages | 6 |
| Date of Issue | 2022-09-06 (LOIS, IE, EMM) |
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