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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI, MICT [detail] | 2021-11-05 15:50 |
Online | Online | [Short Paper]
Sketch-based CT image generation of lung cancers using Pix2pix
-- An attempt to improve representation by adopting Style Blocks -- Ryo Toda, Atsushi Teramoto (FHU), Masakazu Tsujimoto (FHUH), Hiroshi Toyama, Masashi Kondo, Kazuyoshi Imaizumi, Kuniaki Saito (FHU), Hiroshi Fujita (Gifu Univ.)  MICT2021-42 MI2021-40 |
Generative adversarial networks (GAN) have been used to overcome the lack of data in medical images. However, such appli... [more] | MICT2021-42 MI2021-40 pp.66-67 |
| CAS, NLP | 2021-10-14 15:50 |
Online | Online | Implementation of a Generative Adversarial Network as Bitwise Neural Network Takuma Matsuno, Gauthier Lovic (Ariake College) CAS2021-28 NLP2021-26 |
Generative Adversarial Network (GAN) is an artificial intelligence algorithm in which a generative network, which produc... [more] | CAS2021-28 NLP2021-26 pp.62-67 |
| PRMU | 2021-10-09 09:00 |
Online | Online | Omni-Directional Image Representation in GAN-based Image Generator Keisuke Okubo, Takao Yamanaka (Sophia Univ.) PRMU2021-17 |
The omni-directional image generation from a snapshot image taken by an ordinary camera has been developed using conditi... [more] | PRMU2021-17 pp.5-10 |
| MI | 2021-03-15 14:30 |
Online | Online | Comparison of Deep Learning Reconstruction for MR Compressed Sensing Shinya Abe, Shohei Ouchi, Satoshi Ito (Utsunomiya Univ.) MI2020-56 |
The theory of compressed sensing (CS) has been introduced to MRI to reduce the scan time. However, CS reconstruction int... [more] | MI2020-56 pp.41-45 |
| MI | 2021-03-17 11:00 |
Online | Online | Optimal Design and Quality Assessment of Color Laparoscopic Super-Resolution Image by Generative Adversarial Networks Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) MI2020-91 |
The Generative Adversarial Networks (GAN) is unsupervised learning enabled to transform according to data characteristic... [more] | MI2020-91 pp.186-190 |
| MI | 2021-03-17 13:45 |
Online | Online | Medical Image Style Translation by Adversarial Training with Paired Inputs Kazuki Fujioka (Kobe Univ.), Takashi Matsubara (Osaka Univ.), Kuniaki Uehara (Osaka Gakuin Univ.) MI2020-96 |
Medical image diagnosis by artificial intelligence requires a large amount of data for learning. However, preparing such... [more] | MI2020-96 pp.212-217 |
| EMM | 2021-03-04 14:45 |
Online | Online | [Poster Presentation]
Improvement of Video Forgery Detection Using Generative Adversarial Networks Yutaro Osako (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2020-72 |
Our work aims to detect tampered objects in the spatial domain of videos with high accuracy. We target videos, including... [more] | EMM2020-72 pp.28-33 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-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] | |
| SR | 2020-11-20 10:25 |
Online | Online | A Radio Map Construction Based on Deep Generative Models with 3 Dimensional map Shinsuke Bannai, Katsuya Suto (UEC) SR2020-40 |
This paper addresses a spatial extrapolation problem in measurement-based radio map construction. Compared to a spatial ... [more] | SR2020-40 pp.114-119 |
| MI | 2020-09-03 10:00 |
Online | Online | Lung region segmentation of thoracoscopic image with unsupervised image translation Jumpei Nitta, Megumi Nakao (Kyoto Univ.), Keiho Imanishi (e-Growth Co. Ltd.), Tetsuya Matsuda (Kyoto Univ.) MI2020-19 |
In endoscopic surgery, it is necessary to understand the three-dimensional structure of the target region to improve saf... [more] | MI2020-19 pp.13-18 |
| MI | 2020-09-03 11:00 |
Online | Online | [Short Paper]
Quantitative analysis of epicardial adipose tissue by two-stage segmentation network and its system development Takayuiki Nagata, Yutaro Iwamoto, Zhao Ziyu (Ritsumeikan Univ), Yuji Tezuka, Hiroki Okada, Kiyosumi Maeda, Atsuyuki Wada, Atsunori Kashiwagi (Kusatsu General Hospital), Yen-Wei Chen (Ritsumeikan Univ) MI2020-23 |
Diabetes is thought to lead to vascular disease and arteriosclerosis, and there is a need for early detection and treatm... [more] | MI2020-23 pp.27-30 |
| MI | 2020-09-03 14:25 |
Online | Online | Proposal of 3D Generative Adversarial Network for Improving Image Ouality of Cone-Beam CT Images Takumi Hase, Megumi Nakao (Kyoto Univ.), Keoho Imanishi (e-Growth Co., Ltd), Mitsuhiro Nakamura, Tetsuya Matsuda (Kyoto Univ.) MI2020-29 |
Artifacts and defects included in Cone-beam CT (CBCT) images have become an obstacle in radiation therapy and surgery su... [more] | MI2020-29 pp.51-56 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-05 11:10 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
Hairstyle Recommendation Considering Facial Attractiveness Yuto Nakamae, Xueting Wang, Toshihiko Yamasaki, Kiyoharu Aizawa (UT) IMQ2019-44 IE2019-126 MVE2019-65 |
(To be available after the conference date) [more] | IMQ2019-44 IE2019-126 MVE2019-65 pp.145-150 |
| EMM | 2020-03-05 15:35 |
Okinawa | (Cancelled but technical report was issued) |
[Poster Presentation]
Personalized font system
-- beautiful character generation with hand writing style -- Yuto Yamamoto, Michiharu Niimi (KIT) EMM2019-115 |
For modern computer society, one may need human touch character font system to enjoy making communication through Intern... [more] | EMM2019-115 pp.69-74 |
| EMM | 2020-03-05 16:45 |
Okinawa | (Cancelled but technical report was issued) |
[Poster Presentation]
Video Forgery Detection Using Generative Adversarial Networks Shoken Ohshiro (Osaka Univ.), Kazuhiro Kono (Kansai Univ.), Noboru Babaguchi (Osaka Univ.) EMM2019-122 |
The purpose of our work is to detect the regions of tampered objects in the spatial domain of videos by passive approach... [more] | EMM2019-122 pp.107-112 |
| NC, MBE (Joint) |
2020-03-05 10:45 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
YuruGAN: Yuru-Charas Generated by Generative Adversarial Networks Yuki Hagiwara, Toshihisa Tanaka (TUAT) NC2019-93 |
Yuru-chara is a mascot character created by local governments and companies for the purpose of publicizing information o... [more] | NC2019-93 pp.101-106 |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 16:20 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
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] | |
| MI | 2020-01-30 10:40 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Evaluation of 3D adversarial networks for metallic dental artifact reduction Megumi Nakao (Kyoto Univ.), Keiho Imanishi (e-Growth), Nobuhiro Ueda (Nara Medical Univ.), Yuichiro Imai (Otowa Hosp.), Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2019-101 |
(To be available after the conference date) [more] | MI2019-101 pp.159-164 |
| EA | 2019-12-12 14:25 |
Fukuoka | Kyushu Inst. Tech. | Performance improvement of speech enhancement network by multitask learning including noise information Haruki Tanaka (NITTC), Yosuke Sugiura, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ.), Ryoichi Miyazaki (NITTC) EA2019-70 |
In the signal processing field, there is a growing interest in speech enhancement.Recently, a lot of speech enhancement ... [more] | EA2019-70 pp.31-36 |
| RISING (2nd) |
2019-11-26 10:30 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
Reconstruction of Occluded Human Skeleton Information Using Generative Adversarial Network Bochao Zhang, Takashi Nishitsuji, Takuya Asaka (Tokyo Metropolitan Univ.) |
Recently, the posture estimation technology using human skeleton data detected by deep learning has attracted attention.... [more] | |
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