Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
IBISML |
2023-12-20 16:25 |
Tokyo |
National Institute of Informatics (Tokyo, Online) (Primary: On-site, Secondary: Online) |
Anomaly detection by deep support data descriptions with pseudo-anomaly data Shuta Tsuchio, Takuya Kitamura (NIT, Toyama college) IBISML2023-34 |
This paper presents deep support vector data description (DSVDD) with pseudo-anomaly data that generated by generative m... [more] |
IBISML2023-34 pp.25-30 |
AI |
2023-09-12 15:35 |
Hokkaido |
(Hokkaido) |
Variational Autoencoder Oriented Protection for Intellectual Property Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) AI2023-31 |
In recent years, generative AI, which generates images based on instructions in natural language, has developed rapidly ... [more] |
AI2023-31 pp.180-186 |
SIP |
2022-08-25 13:21 |
Okinawa |
Nobumoto Ohama Memorial Hall (Ishigaki Island) (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Style Feature Extraction by Contrastive Learning and Mutual Information Constraints Suguru Yasutomi, Toshihisa Tanaka (TUAT) SIP2022-52 |
Extracting style features is crucial for analyzing data. This paper proposes a style feature extraction using variationa... [more] |
SIP2022-52 pp.13-18 |
EA, SIP, SP, IPSJ-SLP [detail] |
2022-03-01 14:45 |
Okinawa |
(Okinawa, Online) (Primary: On-site, Secondary: Online) |
Target speaker extraction based on conditional variational autoencoder and directional information in underdetermined condition Rui Wang, Li Li, Tomoki Toda (Nagoya Univ) EA2021-76 SIP2021-103 SP2021-61 |
This paper deals with a dual-channel target speaker extraction problem in underdetermined conditions. A blind source sep... [more] |
EA2021-76 SIP2021-103 SP2021-61 pp.76-81 |
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] |
2022-02-21 16:45 |
Online |
Online (Online) |
A Note on Disentanglement Using Deep Generative Model Based on Variational Autoencoder
-- Introduction of Regularization Losses Based on Metrics of Disentangled Representation -- Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study disentangled representation learning using a deep generative model based on Variational Autoenco... [more] |
|
R |
2021-06-12 14:25 |
Online |
Online (Zoom) (Online) |
A Study on Dual-task VAE with Weibull distribution for RUL estimation and application to Aero-Propulsion System data Ryosuke Sato, Mitsuhiro Kimura (Hosei Univ.) R2021-12 |
Remaining Useful Life (RUL) is one of the most important assessment measures in reliability engineering.
Although sever... [more] |
R2021-12 pp.7-12 |
SP, EA, SIP |
2020-03-03 09:00 |
Okinawa |
Okinawa Industry Support Center (Okinawa) (Cancelled but technical report was issued) |
Semi-supervised Self-produced Speech Enhancement and Suppression Based on Joint Source Modeling of Air- and Body-conducted Signals Using Variational Autoencoder Shogo Seki, Moe Takada, Kazuya Takeda, Tomoki Toda (Nagoya Univ.) EA2019-140 SIP2019-142 SP2019-89 |
This paper proposes a semi-supervised method for enhancing and suppressing self-produced speech, using a variational aut... [more] |
EA2019-140 SIP2019-142 SP2019-89 pp.225-230 |
KBSE, SC |
2019-11-08 13:30 |
Nagano |
Shinshu University (Nagano) |
Malicious Domain Names Detection Based on TF-IDE and Variational Autoencoder: Classification with Quantum-enhanced Support Vector Machine Yuwei Sun (UTokyo), Ng S. T. Chong (UNU), Hideya Ochiai (UTokyo) KBSE2019-26 SC2019-23 |
With the development of network technology, the use of domain name system (DNS) becomes common. However, the attacks on ... [more] |
KBSE2019-26 SC2019-23 pp.19-23 |
SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 10:25 |
Okinawa |
(Okinawa) |
Non-parallel and Many-to-Many Voice Conversion Using Variational Autoencoder Conditioned by Phonetic Posteriorgrams and d-vectors Yuki Saito (NTT/Univ. of Tokyo), Yusuke Ijima, Kyosuke Nishida (NTT), Shinnosuke Takamichi (Univ. of Tokyo) EA2017-105 SIP2017-114 SP2017-88 |
This paper proposes novel frameworks for non-parallel and many-to-many voice conversion (VC) using variational autoencod... [more] |
EA2017-105 SIP2017-114 SP2017-88 pp.21-26 |
PRMU, BioX |
2018-03-18 16:10 |
Tokyo |
(Tokyo) |
Toward image inbetweening using Latent Model Paulino Cristovao (Univ. of Tsukuba), Yusuke Tanimura, Hidemoto Nakada, Hideki Asoh (AIST) BioX2017-49 PRMU2017-185 |
Image interpolation is a well known problem in computer vision. Many approaches are restricted to optical flow and convo... [more] |
BioX2017-49 PRMU2017-185 pp.79-84 |