| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| ME, IST, IEICE-BioX, IEICE-SIP, IEICE-MI, IEICE-IE [detail] |
2024-06-06
13:45 |
Niigata |
Nigata University (Ekinan-Campus "TOKIMATE") |
Generative AI system for preventing special fraud
Kenta Ide, Shuji Awai, Sho Iwasaki, Megumi Chikano, Takeshi Konno (Fujitsu), Masayuki Kiriu (Toyo Univ.) |
(To be available after the conference date) [more] |
|
| HI |
2024-03-19
15:40 |
Online |
|
Team work engagement improvement support system based on AI Facilitator
Yuuki Yabe, Mutsuo Sano (OIT) |
Recently, there has been a demand for work styles that are conscious of work engagement, including productivity. In this... [more] |
HI2024-28
pp.60-63 |
| AIT, IIEEJ, AS, CG-ARTS |
2024-03-05
13:00 |
Tokyo |
Tokyo University of Technology |
Perception of Response Time in Dialogue Generation AI with Various Fillers
Keiya Shimakage, Hirokazu Yasuhara, Koji Mikami (TUT) |
Interactive character content using sentence generation AI recognizes the user's utterance and then generates a response... [more] |
AIT2024-85
pp.193-195 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
16:45 |
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] |
MMS2022-19 ME2022-44 AIT2022-19
pp.97-102 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
12:45 |
Online |
online |
Regularizing Generative Adversarial Networks with Internal Representation of Generators
Yusuke Hara, Toshihiko Yamasaki (UTokyo) |
In training generative adversarial networks, maintaining the criteria of the discriminator stably is crucial to training... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
15:20 |
Online |
online |
A Note on Electron Microscope Image Generation from Mix Proportion and Material Property via Generative Adversarial Network for Rubber Materials
Rintaro Yanagi, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Estimating the properties of rubber materials from ingredients is necessary to accelerate rubber material development. A... [more] |
MMS2022-27 ME2022-52 AIT2022-27
pp.187-191 |
| ME |
2021-12-13
14:50 |
Online |
online |
Latent expression separation using the locality of changes in the real image
Toshiki Hazama (Ritsumeikan Univ.), Masataka Seo (OIT), Yen-Wei Chen (Ritsumeikan Univ.) |
GAN, a deep generative model, makes a great contribution to the image generation task. However, one of the problems that... [more] |
ME2021-95
pp.29-31 |
| ME |
2021-12-13
15:20 |
Online |
online |
Automatic Generation of Viewpoint Change Video Using Consistent Regularized Generative Adversarial Networks
Kento Otsu (Ritsumeikan Univ.), Masataka Seo (Osaka Institute of Technology Osaka), Yen-Wei Chen (Ritsumeikan Univ.) |
Gaze plays an important role in conversation. However, in a video call system using a personal computer or the like, it ... [more] |
ME2021-96
pp.33-35 |
| BCT, IEICE-SIS |
2021-10-08
11:30 |
Online |
online |
Analysis of Writing Style on Wood Slips of the Chinese Han period Using Deep Generative Model
Chiang Meng Yuan, Soh Yoshida, Takao Fujita, Mitsuji Muneyasu (Kansai Univ.) |
In this paper, we develop a method to objectively analyze the calligraphic styles of wood slips excavated in Northwester... [more] |
|
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-19
14:15 |
Online |
Online |
[Special Talk]
A Note on Electron Microscope Image Generation from Mix Proportion via Conditional Style Generative Adversarial Network for Rubber Materials
Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Estimating the properties of rubber materials from ingredients is necessary to accelerate rubber material development. I... [more] |
MMS2021-22 ME2021-22 AIT2021-22
pp.171-175 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
14:55 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
A Note on Estimation of Image Categories Using Brain Activity While Viewing Images Based on MVBGM-MS
Yusuke Akamatsu (Hokkaido Univ.), Ryosuke Harakawa (Nagaoka Univ. of Tech.), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents multi-view Bayesian generative model for multi-subject fMRI data (MVBGM-MS) for accurate estimation ... [more] |
MMS2020-16 HI2020-16 ME2020-44 AIT2020-16
pp.79-83 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
16:20 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
A Note on Generation of Electron Microscope Images via Auxiliary Classifier Generative Adversarial Network with Mix Proportions
Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we investigate a method for generation of images that represent the internal structure of rubber material... [more] |
MMS2020-21 HI2020-21 ME2020-49 AIT2020-21
pp.107-111 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-28
15:10 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
Unpaired Learning for Noise-free, Scale Invariant, and Interpretable Image Enhancement
Satoshi Kosugi, Toshihiko Yamasaki (Univ. of Tokyo) |
This paper tackles unpaired image enhancement, a task of learning a mapping function which transforms input images into ... [more] |
|
| AIT, IIEEJ, AS, CG-ARTS |
2018-03-16
14:15 |
Tokyo |
Tokyo University of Technology |
A New Expression composed from 2D Animation and Cloth-shaped Generative Art
Syou Takino, Naoya Tsuruta, Kunio Kondou (TUT) |
In recent years, generative art have become popular and used as motion graphics in many video contents including digital... [more] |
AIT2018-145
pp.369-372 |
| IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-16
10:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Use of Generative Adversarial Networks for Gastritis Classification from Gastric X-ray Images
Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents potential of gastritis images generated by generative adversarial networks (GANs) for gastritis clas... [more] |
MMS2018-31 HI2018-31 ME2018-31 AIT2018-31
pp.299-303 |
| AIT, IIEEJ, AS, CG-ARTS |
2017-03-14
15:54 |
Tokyo |
Ochanomizu Univ. |
A Study on the Method of Visual Expression and Production for Achieving Between Surrounded Display Environment and Live Broadcasting
-- Practices on NicoNico Gakkai beta --
Ryuichi Ono (TUT), Hiroshi Takai (garage), Akinori Ito (TUT), Koichiro Eto (AIST) |
From 2011 to 2015, at the “NicoNico Gakkai Beta Symposium” which was held five times in Roppongi Nicofarre. The authors ... [more] |
AIT2017-67
pp.85-88 |
| AIT, IIEEJ, AS |
2013-03-15
16:20 |
Kanagawa |
Keio Univ. |
The town automatic generative system for a game maker
Asahida Takuya, Nakamura Naoto (CIT) |
This system is a town automatic generative system for a game maker. When a user sets a value to each level, the town whi... [more] |
AIT2013-74
pp.143-144 |