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| Presentation | 2023-06-29 15:10 Selective Inference for DNN-driven Saliency Map Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Tomohiro Shiraishi (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN)  NC2023-5 IBISML2023-5 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | The usefulness of image classification using DNN models has been confirmed in various fields, but the prediction mechanism of these models cannot be fully understood. Therefore, a type of methods called Saliency Map has been proposed to visualize the explanation of predictions, but issues regarding the reliability of the results have been pointed out. In this study, we consider evaluating the reliability of Saliency Map using the framework of statistical hypothesis testing. Unfortunately, conventional statistical hypothesis testing cannot perform valid tests due to the selection bias caused by DNNs. Therefore, we introduce the concept of selective inference, which has been actively studied in recent years, and propose a valid testing method that can properly control Type I Error Rate. In this paper, we specifically report the results when the proposed method is applied to saliency maps obtained by Grad-cam, one of the most frequently used Saliency Map techniques. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Selective Inference / Statistical Hypothesis Testing / Saliency Map / Deep Learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 123, no. 91, IBISML2023-5, pp. 30-34, June 2023. | |
| Paper # | IBISML2023-5 | |
| Date of Issue | 2023-06-22 (NC, IBISML) | |
| 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 | NC2023-5 IBISML2023-5 |
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| Conference Information | |
| Committee | NC IBISML IPSJ-BIO IPSJ-MPS |
| Conference Date | 2023-06-29 - 2023-07-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | OIST Conference Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2023-06-NC-IBISML-BIO-MPS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Selective Inference for DNN-driven Saliency Map |
| Sub Title (in English) | |
| Keyword(1) | Selective Inference |
| Keyword(2) | Statistical Hypothesis Testing |
| Keyword(3) | Saliency Map |
| Keyword(4) | Deep Learning |
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| 1st Author's Name | Daiki Miwa |
| 1st Author's Affiliation | Nagoya Institute of Technology (NITech) |
| 2nd Author's Name | Vo Nguyen Le Duy |
| 2nd Author's Affiliation | RIKEN (RIKEN) |
| 3rd Author's Name | Tomohiro Shiraishi |
| 3rd Author's Affiliation | Nagoya University (Nagoya Univ.) |
| 4th Author's Name | Ichiro Takeuchi |
| 4th Author's Affiliation | Nagoya University/RIKEN (Nagoya Univ./RIKEN) |
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| Speaker | Author-1 |
| Date Time | 2023-06-29 15:10:00 |
| Presentation Time | 25 minutes |
| Registration for | IBISML |
| Paper # | NC2023-5, IBISML2023-5 |
| Volume (vol) | vol.123 |
| Number (no) | no.90(NC), no.91(IBISML) |
| Page | pp.30-34 |
| #Pages | 5 |
| Date of Issue | 2023-06-22 (NC, IBISML) |
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