Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
EMT, IEE-EMT |
2023-11-09 10:55 |
Yamaguchi |
Kaikyo Messe Shimonoseki |
On stabilisation of a finite element method for the diffusion equation using expansion of basis functions and the Hilbert transformation Kazuki Niino, Yusuke Takeuchi (Kyoto Univ) EMT2023-62 |
This paper proposes a stabilisation method for a finite element method using the Hilbert-type operator for the heat equa... [more] |
EMT2023-62 pp.1-5 |
RISING (3rd) |
2023-10-31 09:45 |
Hokkaido |
Kaderu 2・7 (Sapporo) |
[Poster Presentation]
Triadic Split Computing toward Privacy-Conscious Generative AI services Shoki Ohta, Takayuki Nishio (Tokyo Tech) |
With the rapid advancements in big AI models such as text and image generation models, numerous web services have begun ... [more] |
|
MIKA (3rd) |
2023-10-10 15:35 |
Okinawa |
Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
A Study on the Information Diffusion via Reposts without Explicit Diffusion Paths on Social Media Yuto Tamura, Sho Tsugawa (Tsukuba Univ.), Kohei Watabe (NUT) |
The spread of information on social media can be understood as a process where one receives information from those they ... [more] |
|
MIKA (3rd) |
2023-10-10 15:35 |
Okinawa |
Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
An Evaluation of the Generalizability of Influencer Prediction Models between Social Networks in Different Domains Kota Tahara, Sho Tsugawa (ITF) |
Identifying influencers on social media is one of the important research issues. Various methods for identifying influen... [more] |
|
NLP, CAS |
2023-10-07 10:50 |
Gifu |
Work plaza Gifu |
Characteristics of traveling waves in inhomogeneous media with FitzHugh-Nagumo model
-- focusing on dispersion relations and percolation transition -- Chikoo Oosawa (Kyushu Inst. of Tech.) CAS2023-51 NLP2023-50 |
Numerical solutions were obtained from FitzHugh-Nagumo(FHN) model in a two-dimensional media. In order to introduce hete... [more] |
CAS2023-51 NLP2023-50 pp.96-99 |
IA |
2023-09-22 12:45 |
Hokkaido |
Hokkaido Univeristy (Primary: On-site, Secondary: Online) |
Development and Evaluation of 3D Spatial Sharing System by Sensor Fusion of LiDAR and RGB Camera Mana Nishigaki, Hiroshi Yamamoto (Ritsumeikan Univ.), Hideaki Miyaji (Ritsumeikan University) IA2023-25 |
With the recent spread of COVID-19, online communication methods are attracting attention. However, the existing methods... [more] |
IA2023-25 pp.89-94 |
AI |
2023-09-12 15:55 |
Hokkaido |
|
Analysis of Conditional Image Generation Methods Using Color Palettes in Animal Personification Task Jianglin Xu, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2023-19 |
With the advent of large-scale pre-trained open-source diffusion models, image generation is now easily accessible to no... [more] |
AI2023-19 pp.101-108 |
AI |
2023-09-12 15:35 |
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 |
AI |
2023-09-12 16:50 |
Hokkaido |
|
Koki Miyauchi, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga (UEC) AI2023-34 |
Icons are indispensable elements for websites and smartphone applications. For website developers, the creation of icons... [more] |
AI2023-34 pp.201-206 |
CQ, MIKA (Joint) (2nd) |
2023-08-30 16:20 |
Fukushima |
Tenjin-Misaki Sports Park |
[Poster Presentation]
Analysis of occurrence patterns in retweets without explicit diffusion paths focusing on the distance between users Yuto Tamura, Sho Tsugawa (Tsukuba Univ.), Kohei Watabe (NUT) |
On social media, it is conceivable that information diffusion is facilitated by the recurrent actions of users who engag... [more] |
|
ITS, IPSJ-ITS, IEE-ITS |
2023-08-29 16:45 |
Kanagawa |
Kanto Gakuin Univ. (Kanazawa-Hakkei Campus) (Primary: On-site, Secondary: Online) |
A Study on evaluation index for step counting of PDR Hana Osawa, Masahiro Fujii (Utsunomiya Univ.) ITS2023-10 |
Pedestrian Dead Reckoning (PDR) is an alternative pedestrian location estimation method for indoor when GNSS (Global Nav... [more] |
ITS2023-10 pp.16-21 |
MSS, CAS, SIP, VLD |
2023-07-07 15:20 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Verification of effectiveness of the greedy algorithm for the influence maximization problem focusing on the authenticity in OSN Jodai Yoshiue, Atsushi Wakamatsu, Masaaki Miyasita, Norihiko Shinomiya (Soka Univ.) CAS2023-28 VLD2023-28 SIP2023-44 MSS2023-28 |
In recent years, social media has become increasingly popular. While it has advantages such as high advertising effectiv... [more] |
CAS2023-28 VLD2023-28 SIP2023-44 MSS2023-28 pp.143-146 |
MI |
2023-07-03 10:00 |
Miyagi |
Tohoku Univ. Sakura Hall |
HCP data processing by hybrid approach for parameter inference in free water imaging model of diffusion MRI
-- comparison of diffusion tensor computation methods for datasets without b0 image -- Yoshitaka Masutani (Tohoku Univ.), Keigo Yamazaki, Wataru Uchida, Koji Kamagata (Juntendo Univ.), Koh Sasaki (HHC), Shigeki Aoki (Juntendo Univ.) MI2023-7 |
We have proposed a hybrid approach combining synthetic Q-space learning and conventional fitting for parameter estimatio... [more] |
MI2023-7 pp.1-2 |
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2023-06-30 14:45 |
Okinawa |
OIST Conference Center (Primary: On-site, Secondary: Online) |
Diffusion model with MASKed input for generating gestures during dyadic conversation Yuya Okadome (TUS), Yutaka Nakamura (Riken) NC2023-19 IBISML2023-19 |
In a dyadic conversation scene, it is necessary to consider not only the behavior of one person but not also that of a c... [more] |
NC2023-19 IBISML2023-19 pp.121-128 |
MVE, IPSJ-HCI, IPSJ-EC, VRSJ, ITE-HI, HI-SIG-DeMO |
2023-06-01 14:50 |
Tokyo |
(Primary: On-site, Secondary: Online) |
relationship between the difficulty of binocular fusion and limitation to the observing iris size in stereo-parallax display Daiki Nokura, Ryugo Kijima (Gifu Univ.) MVE2023-10 |
Two functions in human eye, the vergence and the accommodation are linked together in natural environment. Stereoscopic ... [more] |
MVE2023-10 pp.51-56 |
PRMU, IPSJ-CVIM |
2023-05-18 13:30 |
Aichi |
(Primary: On-site, Secondary: Online) |
Image Harmonization Using Diffusion Model for Perceptual Quality Improvement Taito Naruki, Norimichi Ukita (TTI) PRMU2023-1 |
Image harmonization is the task of eliminating the discomfort of color tones that occurs when images are composited. How... [more] |
PRMU2023-1 pp.1-5 |
PRMU, IPSJ-CVIM |
2023-05-19 09:50 |
Aichi |
(Primary: On-site, Secondary: Online) |
Incorporating Signed Distance Fields to Improve Text-to-3D Generation Zhuofan Sun, Daichi Horita (Univ. of Tokyo), Satoshi Ikehata (NII), Kiyoharu Aizawa (Univ. of Tokyo) PRMU2023-9 |
Frameworks for generating 3D objects from text description have been proposed in recent years. These frameworks utilize ... [more] |
PRMU2023-9 pp.45-50 |
CCS |
2023-03-27 09:00 |
Hokkaido |
RUSUTSU RESORT |
Medical Image Segmentation with Inverse Heat Dissipation Model Yu Kashihara, Takashi Matsubara (Osaka Univ.) CCS2022-82 |
The diffusion model is a generative model based on stochastic transitions and has been successfully used to generate
an... [more] |
CCS2022-82 pp.107-112 |
NLP, MSS |
2023-03-17 10:20 |
Nagasaki |
(Primary: On-site, Secondary: Online) |
A method of suppressing false information diffusion in OSN Atsushi Wakamatsu, Masaaki Miyashita, Norihiko Shinomiya (Soka Univ.) MSS2022-95 NLP2022-140 |
The diffusion of false information in online social networks is a serious problem.Despite various countermeasures, it is... [more] |
MSS2022-95 NLP2022-140 pp.156-159 |
NC, MBE (Joint) |
2023-03-15 10:30 |
Tokyo |
The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Proposal of Node Fusion in Sparse DenseNet Shogo Taneda, Shoma Noguchi, Yukari Yamauchi (Nihon Univ.) NC2022-110 |
Gao Huang et al. proposed a deep learning model called DenseNet. This deep learning model successfully prevents informat... [more] |
NC2022-110 pp.105-108 |