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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 151  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
RCC, ISEC, IT, WBS 2024-03-13
16:35
Osaka Osaka Univ. (Suita Campus) A Study on Polar Codes Design with Robustness against Channel SNR Fluctuation
Hidetake Matsui, Hideki Ochiai (YNU) IT2023-102 ISEC2023-101 WBS2023-90 RCC2023-84
Polar codes are known to achieve high reliability with low decoding complexity. The design of polar codes requires the s... [more] IT2023-102 ISEC2023-101 WBS2023-90 RCC2023-84
pp.179-184
RCC, ISEC, IT, WBS 2024-03-14
13:00
Osaka Osaka Univ. (Suita Campus) [Special Invited Talk] Smart Radio and Reliable Communication & Control -- A Journey Through Research and Emerging Challenges --
Masaaki Katayama (Nagoya Univ.) RCS2023-276 SR2023-99 SRW2023-63 IT2023-117 ISEC2023-116 WBS2023-105 RCC2023-99
In Smart Radio, traditional hard-fixed circuits are realized using flexible devices and computers, marking the integrati... [more] RCS2023-276 SR2023-99 SRW2023-63 IT2023-117 ISEC2023-116 WBS2023-105 RCC2023-99
p.125(RCS), p.57(SR), p.90(SRW), p.266(ISEC), p.266(WBS), p.266(RCC)
SIP, SP, EA, IPSJ-SLP [detail] 2024-02-29
10:10
Okinawa
(Primary: On-site, Secondary: Online)
Noise-Robust Voice Conversion by Denoising Training Conditioned with Latent Variables of Speech Quality and Recording Environment
Takuto Igarashi, Yuki Saito, Kentaro Seki, Shinnosuke Takamichi (UT), Ryuichi Yamamoto, Kentaro Tachibana (LY), Hiroshi Saruwatari (UT) EA2023-63 SIP2023-110 SP2023-45
In this paper, we propose noise-robust voice conversion by conditioning latent variables representing speech quality and... [more] EA2023-63 SIP2023-110 SP2023-45
pp.13-18
NS, IN
(Joint)
2024-02-29
09:20
Okinawa Okinawa Convention Center Performance Improvement and Traceability Validation of Service Mesh based C-plane for Robust 5GC
Kenji Kanai (UTokyo), Shiku Hirai (NTT), Akihiro Nakao (UTokyo) NS2023-210
Robust first-mile wireless communication systems, such as 5G and Beyond 5G, are essential for a robust ICT infrastructur... [more] NS2023-210
pp.224-229
IN, IA
(Joint)
2023-12-22
15:00
Hiroshima Satellite Campus Hiroshima [Short Paper] A Study on the Applicability of Graph Reduction to Evaluating the Robustness of Complex Networks
Murakawa Yamato, Ryotaro Matsuo, Ryo Nakamura (Fukuoka Univ.) IA2023-53
Generally, the computational complexity of network simulation and machine learning based on graph structure such as GNN ... [more] IA2023-53
pp.48-52
SS, DC 2023-10-12
10:25
Nagano
(Primary: On-site, Secondary: Online)
Robustness trends of DP-SGD, a machine learning with differential privacy
Takahiro Kanki, Shinpei Ogata, Kozo Okano (Sinshu Univ), Shin Nakajima (NII) SS2023-28 DC2023-34
Although machine learning has been successful in various fields, there is a problem that an adversary can extract traini... [more] SS2023-28 DC2023-34
pp.38-43
EMM, BioX, ISEC, SITE, ICSS, HWS, IPSJ-CSEC, IPSJ-SPT [detail] 2023-07-24
14:20
Hokkaido Hokkaido Jichiro Kaikan A Generic Construction of Outsider Anonymous Broadcast Encryption with Keyword Search
Keita Emura (NICT), Kaisei Kajita, Go Ohtake (NHK) ISEC2023-22 SITE2023-16 BioX2023-25 HWS2023-22 ICSS2023-19 EMM2023-22
Broadcast encryption with keyword search (BEKS) has been proposed (Attrapadung et al. at ASIACRYPT 2006/Chatterjee-Mukhe... [more] ISEC2023-22 SITE2023-16 BioX2023-25 HWS2023-22 ICSS2023-19 EMM2023-22
pp.52-59
NC, MBE
(Joint)
2023-03-15
11:20
Tokyo The Univ. of Electro-Communications
(Primary: On-site, Secondary: Online)
Optimizing SOINN Space for High-Dimensional Data Robustness
Yu Takahagi, Yusuke Tsuchida, Yukari Yamauchi (Nihon Univ.) NC2022-112
Yamazaki et al. proposed a learning method called Self-Organizing Incremental Neural Network (SOINN). This method is an ... [more] NC2022-112
pp.113-118
HWS, VLD 2023-03-02
14:15
Okinawa
(Primary: On-site, Secondary: Online)
[Memorial Lecture] DependableHD: A Hyperdimensional Learning Framework for Edge-oriented Voltage-scaled Circuits [Memorial lecture]
Dehua Liang (Osaka Univ.), Hiromitsu Awano (Kyoto Univ.), Noriyuki Miura, Jun Shiomi (Osaka Univ.) VLD2022-93 HWS2022-64
Voltage scaling is a promising approach for energy efficiency but also brings challenges to guaranteeing stable circuit ... [more] VLD2022-93 HWS2022-64
p.111
R 2022-11-17
15:25
Online Online Process capability index for reliability evaluation
Toshinari Mastsuoka (MELCO) R2022-43
Optimize the tolerance limits of the process capability index to obtain the reliability to achieve the target quality. [more] R2022-43
pp.17-22
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-13
14:50
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Investigation of noise removal using U-Net and voice recognition performance improvement -- for train running noise --
Jian Lin, Shota Sano, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2022-26
A method for converting noisy sound into images to remove the noise has been proposed. We are attempting to remove train... [more] SeMI2022-26
pp.34-39
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2022-06-27
15:30
Okinawa
(Primary: On-site, Secondary: Online)
Evaluating and Enhancing Reliabilities of AI-Powered Tools -- Adversarial Robustness --
Jingfeng Zhang (RIKEN-AIP) NC2022-4 IBISML2022-4
When we deploy models trained by standard training (ST), they work well on natural test data. However, those models cann... [more] NC2022-4 IBISML2022-4
pp.20-46
IT, EMM 2022-05-17
15:05
Gifu Gifu University
(Primary: On-site, Secondary: Online)
Generating patch-wise adversarial examples for avoidance of face recognition system and verification of its robustness
Hiroto Takiwaki, Minoru Kuribayashi, Nobuo Funabiki (Okayama univ.) IT2022-5 EMM2022-5
Advances in machine learning technologies such as Convolutional Neural Networks (CNN) have made it possible to identify ... [more] IT2022-5 EMM2022-5
pp.23-28
IBISML 2022-03-08
10:25
Online Online Robust computation of optimal transport by β-potential regularization
Shintaro Nakamura (Univ. Tokyo), Han Bao (Univ.Tokyo/RIKEN), Masashi Sugiyama (RIKEN/Univ. Tokyo) IBISML2021-31
Optimal transport (OT) has become a widely used tool to measure the discrepancy between probability distributions
in th... [more]
IBISML2021-31
pp.8-14
SeMI 2022-01-20
14:20
Nagano
(Primary: On-site, Secondary: Online)
[Short Paper] Estimation of Sound Environment in Room by applying to Transfer Learning using Spectrograms Images
Shota Sano, Yuusuke Kawakita, Tsuyoshi Miyazaki, Hiroshi Tanaka (KAIT) SeMI2021-57
A variety of environmental sounds exist in a room, and the classification of these sounds can be expected to have variou... [more] SeMI2021-57
pp.22-25
AP, WPT
(Joint)
2022-01-21
09:25
Tottori Kenmin-Fureai-Kaikan
(Primary: On-site, Secondary: Online)
Research on MACKEY II with Enhanced Robustness
Keisuke Miyashita, Shigeru Makino, Kenji Itoh (Kanazawa Institute of Tec.) AP2021-148
The Meta-surface inspired Antenna Chip developed by KIT EOE Laboratory (MACKEY, Wi-Fi 2.4GHz band) is an electrically sm... [more] AP2021-148
pp.75-79
IBISML 2020-10-20
14:00
Online Online [Invited Talk] *
IBISML2020-13
We introduce density power divergence, gamma-divergence and H"{o}lder divergence, which enable us to make robust estimat... [more] IBISML2020-13
p.29
IBISML 2020-10-22
14:25
Online Online Improvement of the robustness by increasing the size of feedback vertex set
Masaki Chujyo, Yukio Hayashi (JAIST) IBISML2020-31
Many real world networks such as power grid and communication networks are commonly scale-free, but highly vulnerable ag... [more] IBISML2020-31
pp.55-60
CQ 2020-09-03
10:30
Osaka Osaka University Nakanoshima Center
(Primary: On-site, Secondary: Online)
Analysis of Content Availability at Network Failure in Information-Centric Networking
Ryo Nakamura, Noriaki Kamiyama (Fukuoka Univ.) CQ2020-34
In recent years, ICN (Information-Centric Networking) has been under the spotlight as a network that mainly focuses on t... [more] CQ2020-34
pp.1-6
PRMU, IPSJ-CVIM 2020-03-16
15:25
Kyoto
(Cancelled but technical report was issued)
Assessing robustness of deep learning methods in dermoscopic workflow
Sourav Mishra (Univ. of Tokyo), Hideaki Imaizumi (exMedio), Toshihiko Yamasaki (Univ. of Tokyo) PRMU2019-79
Our paper aims to evaluate current deep learning methods for clinical workflow in the domain of dermatology. Although de... [more] PRMU2019-79
pp.77-78
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