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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IA, SITE, IPSJ-IOT [detail] | 2024-03-13 13:40 |
Okinawa | Miyakojima City Future Creation Center (Primary: On-site, Secondary: Online) |
A Steganalysis of Image Steganography using Real Image Denoising Shinnosuke Toguchi, Takamichi Miyata (CIT)  SITE2023-100 IA2023-106 |
Image steganography is a technique for embedding secret messages in images. SteganoGAN, one of the previous methods, use... [more] | SITE2023-100 IA2023-106 pp.195-202 |
| EMM | 2024-01-16 14:50 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Development of Smartphone App of an application of EmoEditor (Emotion-Expressive Editor) to mail communications Yuki Shimamura, Michiharu Niimi (KIT) EMM2023-82 |
We report the implementation of an emotion-expressive editor, EmoEditor, which enables emotion expression through font c... [more] | EMM2023-82 pp.13-18 |
| IBISML | 2023-12-20 16:25 |
Tokyo | National Institute of Informatics (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 |
| 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 |
|
| EMM, ITE-ME, IE, LOIS, IEE-CMN, IPSJ-AVM [detail] | 2023-09-07 17:10 |
Osaka | Osaka Metropolitan University - Nakamozu Campus- (Hybrid) (Primary: On-site, Secondary: Online) |
Font Generation based on class labels by StyleGAN2 Yuki Shimamura, Michiharu Niimi (KIT) LOIS2023-11 IE2023-21 EMM2023-58 |
Text is an important media to convey informations. Text is used in Communications. But it is difficlt to convey our emot... [more] | LOIS2023-11 IE2023-21 EMM2023-58 pp.22-27 |
| 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 |
| ICTSSL, CAS | 2023-01-27 11:25 |
Tokyo | TBD (Primary: On-site, Secondary: Online) |
On automatic illustrations generated by GAN networks Aika Honne, Kazuya Ozawa, Hideaki Okazaki (SIT) CAS2022-83 ICTSSL2022-47 |
In this report, we discuss automatic illustrations generated by GAN networks (adversarial generative networks). First, a... [more] | CAS2022-83 ICTSSL2022-47 pp.104-107 |
| PRMU | 2022-12-16 14:40 |
Toyama | Toyama International Conference Center (Primary: On-site, Secondary: Online) |
Data Augmentation Shumpei Takezaki (Kyushu Univ.), Kiyohito Tanaka (Kyoto Second Red Cross Hospital), Seiichi Uchida, Takeaki Kadota (Kyushu Univ.) PRMU2022-50 |
Disease severity regression by a convolutional neural network (CNN) for medical images requires a sufficient number of i... [more] | PRMU2022-50 pp.95-99 |
| AI | 2022-07-04 16:50 |
Hokkaido | (Primary: On-site, Secondary: Online) |
A generative model for generation of playable levels in 2D video games. Soichiro Takata, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2022-16 |
(To be available after the conference date) [more] | AI2022-16 pp.82-87 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-28 10:05 |
Okinawa | (Primary: On-site, Secondary: Online) |
Learning Attribute Vector Fields in GAN Latent Space Takehiro Aoshima, Takashi Matsubara (Osaka Univ.) NC2022-12 IBISML2022-12 |
Generative Adversarial Networks (GANs) can generate a great variety of high-quality images. Despite their ability to g... [more] |
NC2022-12 IBISML2022-12 pp.94-99 |
| SP, IPSJ-MUS, IPSJ-SLP [detail] | 2022-06-17 15:00 |
Online | Online | SP2022-13 |
We investigate the method for unsupervised learning of artifacts correction networks used for post-processing of Multi B... [more] | SP2022-13 pp.49-54 |
| SIS, IPSJ-AVM | 2022-06-09 15:00 |
Fukuoka | KIT(Wakamatsu Campus) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Advanced applications of machine learning techniques towards high-performance and cost-effective visual inspection AI Terumasa Tokunaga (Kyutech) SIS2022-6 |
Visual inspection is an essential step for quality control in manufacturing. Recently, many researchers have shown great... [more] | SIS2022-6 p.30 |
| EMM | 2022-03-07 15:00 |
Online | (Primary: Online, Secondary: On-site) (Primary: Online, Secondary: On-site) |
[Poster Presentation]
Music pattern for brain wave activity using Generative Adversarial Network Takumi Wada, Midori Nagai, Hyunho Kang (NITTC) EMM2021-99 |
(To be available after the conference date) [more] | EMM2021-99 pp.40-45 |
| EMM | 2022-03-07 15:25 |
Online | (Primary: Online, Secondary: On-site) (Primary: Online, Secondary: On-site) |
[Poster Presentation]
A Proposal for Emotion-Expressive Editor:EmoEditor by Font Changing Yuuki Shimamura, Michiharu Niimi (KIT) EMM2021-100 |
Text media is one of important ways in communications on computers. For example, email, LINE or Twitter uses it frequent... [more] | EMM2021-100 pp.46-51 |
| CNR, BioX | 2022-03-04 14:20 |
Online | Online | Synthesizing Deep Master Voices for Wolf Attacking on Speaker Recognition Systems Jun Tsuchiya, Masakatsu Nishigaki, Tetsushi Ohki (Shizuoka Univ.) BioX2021-53 CNR2021-34 |
In this paper, we propose an attack on speaker verification systems by Deep Master Voice using GAN-based wolf voice.GAN-... [more] | BioX2021-53 CNR2021-34 pp.33-38 |
| CNR, BioX | 2022-03-04 15:50 |
Online | Online | Gait-based Age Estimation Using Angle Suppression Learning Kodai Yamano (Osaka Univ.), Daigo Muramatsu (Seikei Univ.), Noriko Takemura, Yasushi Yagi (Osaka Univ.) BioX2021-56 CNR2021-37 |
Robustness for observation view difference is an important and expected property for gait-based age estimation. In order... [more] | BioX2021-56 CNR2021-37 pp.51-56 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 12:45 |
Online | Online | Regularizing Generative Adversarial Networks with Internal Representation of Generators Yusuke Hara, Toshihiko Yamasaki (UTokyo) ITS2021-29 IE2021-38 |
In training generative adversarial networks, maintaining the criteria of the discriminator stably is crucial to training... [more] | ITS2021-29 IE2021-38 pp.25-30 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [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] | |
| MI | 2022-01-26 13:00 |
Online | Online | Relationship between Image Quality and Learning Effect in Color Laparoscopic Images Generation by Generative Adversarial Networks Norifumi Kawabata (Hokkaido Univ.), Toshiya Nakaguchi (Chiba Univ.) MI2021-59 |
Improving of personal computer performance, it is possible for healthcare workers and related researchers to support for... [more] | MI2021-59 pp.59-64 |
| AI | 2021-12-13 10:00 |
Fukuoka | Aimattain Hakata station (Primary: On-site, Secondary: Online) |
Easy Level Generation in 2D Action Game with Deep Reinforcement Learning Soichiro Takata, Akihiko Ohsuga, Yasuyuki Tahara, Yuichi Sei (UEC) AI2021-1 |
(To be available after the conference date) [more] | AI2021-1 pp.1-6 |
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