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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CAS, CS | 2024-03-15 14:20 |
Okinawa | Recoloring aware Countermeasure against Adversarial Examples Chisei Ishida, Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.)  CAS2023-134 CS2023-127 |
Adversarial Examples(AEs) which cause artificial intelligence (AI) to make a false prediction by embedded slight perturb... [more] | CAS2023-134 CS2023-127 pp.128-133 |
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| RCC, ISEC, IT, WBS | 2024-03-13 09:15 |
Osaka | Osaka Univ. (Suita Campus) | Performance Evaluation of Visible Light Communication System Using Imaginary Images based Image Classifier Masataka Naito, Tadahiro Wada, Kaiji Mukumoto (Shizuoka Univ.), Hiraku Okada (Nagoya Univ.) IT2023-78 ISEC2023-77 WBS2023-66 RCC2023-60 |
For visible light communication systems that utilizes machine learning-based image classifiers for information embedding... [more] | IT2023-78 ISEC2023-77 WBS2023-66 RCC2023-60 pp.20-25 |
| RCC, ISEC, IT, WBS | 2024-03-14 10:20 |
Osaka | Osaka Univ. (Suita Campus) | Improving classification accuracy of imaged malware through data expansion Kaoru Yokobori, Hiroki Tanioka, Masahiko Sano, Kenji Matsuura, Tetsushi Ueta (Tokushima Univ.) IT2023-115 ISEC2023-114 WBS2023-103 RCC2023-97 |
Although malware-based attacks have existed for years, malware infections increased in 2019 and 2020. One of the reaso... [more] |
IT2023-115 ISEC2023-114 WBS2023-103 RCC2023-97 pp.259-264 |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-04 09:12 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Creating Adversarial Examples to Deceive Both Humans and Machine Learning Models Ko Fujimori (Waseda Univ.), Toshiki Shibahara (NTT), Daiki Chiba (NTT Security), Mitsuaki Akiyama (NTT), Masato Uchida (Waseda Univ.) PRMU2023-65 |
One of the vulnerability attacks against neural networks is the generation of Adversarial Examples (AE), which induce mi... [more] | PRMU2023-65 pp.82-87 |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-04 09:36 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Disabling Adversarial Examples through Color Information Processing Ryo Soeda, Masato Uchida (Waseda Univ.) PRMU2023-67 |
Image classification using neural networks is expected to have a wide range of applications, including automated driving... [more] | PRMU2023-67 pp.94-99 |
| MI | 2024-03-04 09:00 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Distance-informed adversarial learning for metal artifact reduction Daisuke Shigemori, Megumi Nakao (Kyoto Univ.) MI2023-62 |
In this study, we propose an adversarial learning framework that utilises distance information from metal to reduce CT m... [more] | MI2023-62 pp.95-98 |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-04 10:52 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Illust Protection against Generative AI using DnCNN Yukiya Fukuda, Daiju Kanaoka (Kyutech), Hakaru Tamukoh (Kyutech/Research Center for Neuromorphic AI Hardware) PRMU2023-71 |
Although generative AI such as stable diffusion are rapidly developing, but there are concerns about problems such as un... [more] | PRMU2023-71 pp.116-121 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 10:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Multi-task learning with age information model for highly accurate elderly speech recognition. Shine Takumi, Kinouchi Takahiro, Wakabayashi Yukoh, Kitaoka Norihide (TUT) EA2023-64 SIP2023-111 SP2023-46 |
The speech recognition of the elderly is less accurate, especially in smart speaker speech recognition, due to aging-rel... [more] | EA2023-64 SIP2023-111 SP2023-46 pp.19-24 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Black-Box Adversarial Attack for Math Formula Recognition Model Haruto Namura, Masatomo Yoshida (Doshisha Univ.), Nicola Adami (UNIBS), Masahiro Okuda (Doshisha Univ.) EA2023-110 SIP2023-157 SP2023-92 |
Remarkable advances in deep learning have greatly improved the accuracy of image analysis. The progress of deep learning... [more] | EA2023-110 SIP2023-157 SP2023-92 pp.289-293 |
| SeMI, IPSJ-UBI, IPSJ-MBL | 2024-02-29 15:10 |
Fukuoka | Evaluation Experiment of Display Camera Visible Light Communication Using Adversarial Examples on a Monocular Depth Estimation Model Changseok Lee, Hiraku Okada (Nagoya Univ.), Tadahiro Wada (Shizuoka Univ.), Chedlia Ben Naila, Masaaki Katayama (Nagoya Univ.) SeMI2023-75 |
Hidden display-camera visible light communication is a method of embedding data in visual information such as images and... [more] | SeMI2023-75 pp.25-30 |
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| ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2024-02-19 10:45 |
Hokkaido | Hokkaido Univ. | Brightness Adjustment based Countermeasure against Adversarial Examples Takumi Tojo, Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) ITS2023-47 IE2023-36 |
Recently, image classification using deep learning AI has been used for in-vehicle AI, and its accuracy and response spe... [more] | ITS2023-47 IE2023-36 pp.7-12 |
| ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2024-02-19 11:00 |
Hokkaido | Hokkaido Univ. | Improving Adversarial Robustness in Continual Learning Koki Mukai, Soichiro Kumano (UTokyo), Nicolas Michel (UGE/CNRS/LIGM), Ling Xiao, Toshihiko Yamasaki (UTokyo) ITS2023-48 IE2023-37 |
The goal of continual learning is to prevent catastrophic forgetting. However, few studies have simultaneously considere... [more] | ITS2023-48 IE2023-37 pp.13-18 |
| SIP, IT, RCS | 2024-01-19 13:30 |
Miyagi | (Primary: On-site, Secondary: Online) |
[Invited Talk]
Problem of Adversarial Attacks on CNN-based Image Classifiers and Countermeasures Minoru Kuribayashi (Tohoku Univ.) IT2023-67 SIP2023-100 RCS2023-242 |
It is well-known that discriminative models based on deep learning techniques may cause misclassification if adversarial... [more] | IT2023-67 SIP2023-100 RCS2023-242 p.204 |
| EMM | 2024-01-17 11:20 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
A study on 3D model adaptation for generating patch-based adversarial perturbations Hiroto Takiwaki (Okayama Univ.), Minoru Kuribayashi (Touhoku Univ.), Nobuo Funabiki (Okayama Univ.) EMM2023-88 |
The development of facial recognition technology using machine learning has made it possible to recognize individuals fr... [more] | EMM2023-88 pp.44-49 |
| MI, MICT | 2023-11-14 15:20 |
Fukuoka | Generation of pseudo-CT images from phalanges CR images based on deep learning
-- Accuracy comparison using pix2pix and CycleGAN -- Rensuke Ueno, Takaharu Yamazaki (SIT), Kazuaki Tanaka (Neomedical Corporation), Keizo Fukumoto (Saitama Jikei Hospital) MICT2023-35 MI2023-28 |
In this study, we perform generation to pseudo-CT images from phalanges CR images using deep learning. For the image gen... [more] | MICT2023-35 MI2023-28 pp.41-44 |
|
| MIKA (3rd) |
2023-10-11 14:30 |
Okinawa | Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Detecting Poisoning Attacks Using Adversarial Examples in Deep Phishing Detection Koko Nishiura, Tomotaka Kimura, Jun Cheng (Doshisha Univ.) |
In recent years, the convenience of online services has greatly improved, but the number of phishing scams has skyrocket... [more] | |
| NS, IN, CS, NV (Joint) |
2023-09-08 09:00 |
Miyagi | Tohoku University (Primary: On-site, Secondary: Online) |
Demonstrating Data Poisoning Attacks on Machine Learning Models with Multi-Sensor Inputs Shyam Maisuria, Yuichi Ohsita, Masayuki Murata (Osaka Univ.) IN2023-31 |
Data poisoning attacks pose a significant threat to the integrity and reliability of machine learning models. These atta... [more] | IN2023-31 pp.8-13 |
| RCC, ISEC, IT, WBS | 2023-03-14 09:50 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
A Proposal of Visible Light Communication System using Image Classifier based on Imaginary Images Masataka Naito, Tadahiro Wada, Kaiji Mukumoto (Shizuoka Univ.), Hiraku Okada (Nagoya Univ.) IT2022-70 ISEC2022-49 WBS2022-67 RCC2022-67 |
We have proposed a new method of information embedding in visible light communication by using an image classifier based... [more] | IT2022-70 ISEC2022-49 WBS2022-67 RCC2022-67 pp.13-18 |
| ICSS, IPSJ-SPT | 2023-03-13 14:20 |
Okinawa | Okinawaken Seinenkaikan (Primary: On-site, Secondary: Online) |
Dynamic Analysis of Adversarial Attacks Kentaro Goto (JPNIC), Masato Uchida (Waseda Univ.) ICSS2022-52 |
In this study, we propose a method for identifying the characteristics of attack methods by operating them as “samples” ... [more] | ICSS2022-52 pp.25-30 |
| MI | 2023-03-07 15:12 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Conversion to pseudo-CT images from phalanges CR images using adversarial generation networks Tomoaki Ushikoshi, Takaharu Yamazaki (SIT), Kazuaki Tanaka (Neomedical), Keizo Fukumoto (Saitama Jikei Hospital) MI2022-119 |
In this study, we perform conversion to pseudo-CT images from phalanges CR images using adversarial generative network. ... [more] | MI2022-119 pp.184-189 |
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