| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| AIT, IIEEJ, AS, CG-ARTS |
2024-03-05
14:30 |
Tokyo |
Tokyo University of Technology |
Card game AI applying reinforcement learning with Unity ML-Agents
Tatsuya Watanabe, Junichi Yamamoto (THCU) |
In recent years, there has been active research in game AI, with AI agents reaching the level of professional players in... [more] |
AIT2024-138
pp.375-376 |
| IEICE-EID, IDY, IEE-EDD, SID-JC, IEIJ-SSL [detail] |
2024-01-25
13:15 |
Kyoto |
(Primary: On-site, Secondary: Online) |
[Poster Presentation]
Reproduction of changes in membrane potential of neurons by synaptic devices using memristors
Kenta Yachida, Yoshiya Abe, Kazuki Sawai (Ryukoku Univ.), Tokiyoshi Matsuda (Kindai Univ./Ryukoku Univ.), Hidenori Kawanishi (Ryukoku Univ.), Mutsumi Kimura (Ryukoku Univ./NAIST) |
We attempted to replicate the changes in the membrane potential of neurons using thin-film neuromorphic devices that int... [more] |
|
| IEICE-CPM, IEICE-MRIS, IEICE-OME, MMS [detail] |
2023-10-26
13:00 |
Niigata |
(Primary: On-site, Secondary: Online) |
[Invited Talk]
Development of magneto-optical diffractive deep neural network device
Takayuki Ishibashi, Hotaka Sakaguchi, Jian Zhang, Fatima Chafi Zhara (Nagaoka Univ. Tech.), Hirofumi Nonaka (Aichi Inst. Tech.), Satoshi Sumi, Hiroyuki Awano (Toyota Tech. Inst.N) |
We propose a magneto-optical diffractive deep neural network (MO-D2NN). We simulated several MO-D2NNs, each of which con... [more] |
MMS2023-38
pp.1-2 |
| IEICE-SIS, BCT |
2023-10-13
09:30 |
Yamaguchi |
HISTORIA UBE
(Primary: On-site, Secondary: Online) |
[Invited Talk]
Material reservoir computing devices for robot applications, such as in-sensor tactile computing devices
Hirofumi Tanaka (Kyutech) |
Reservoir arithmetic elements, which are expected to be used as lighter-task AI hardware systems, were fabricated in ran... [more] |
|
| AIT, 3DMT, OSJ-HODIC |
2023-09-08
17:15 |
Tokyo |
Nihon Univ. College of Science and Technology (Surugadai Campus) |
|
Phase unwrapping is a technique used to recover the original phase from the wrapped phase in the range (−π, π]. Conventi... [more] |
AIT2023-147 3DMT2023-34
pp.33-36 |
| ME, IEICE-EMM, IEICE-IE, IEICE-LOIS, IEE-CMN, IPSJ-AVM [detail] |
2023-09-07
09:50 |
Osaka |
Osaka Metropolitan Univ.
(Primary: On-site, Secondary: Online) |
Improving Performance of Convolutional Neural Network-Based Driver Behavior Recognition
Shengbiao Wang, Koji Iwano (Tokyo City Univ.) |
This study investigates the automatic recognition of driver behaviors using images captured by in-vehicle cameras for th... [more] |
ME2023-90
pp.7-12 |
| BCT, IEEE-BT, HOKKAIDO |
2023-07-28
11:50 |
Hokkaido |
Sapporo Business Innovation Center
(Primary: On-site, Secondary: Online) |
An Evaluation of Neural Network Parameters for Decoding (8,4) and (16,8) Polar Codes
Reona Kumaki, Hiroshi Tsutsui, Takeo Ohgane (Hokkaido Univ.) |
Polar codes are one type of error correction codes.
When operated with a sufficiently long code length, polar codes ca... [more] |
BCT2023-61
pp.49-52 |
| IST |
2023-06-21
14:10 |
Tokyo |
Tokyo University of Science Morito Memorial Hall |
[Poster Presentation]
Verification of the effectiveness of multitask learning for demosaicking and white-balancing
Yuki Nakagomi, Ryoya Takeuchi, Taishi Iriyama, Takashi Komuro (Saitama Univ) |
In this study, we conducted an investigation on the learning effectiveness of jointly training demosaicking and white ba... [more] |
IST2023-25
pp.19-22 |
| IIEEJ, AIT |
2023-06-03
14:30 |
Tokyo |
TOKYO CITY UNIVERSITY
(Primary: On-site, Secondary: Online) |
Video Encoding Scheme Using Autoencoder with Learning Decoded Image of Previous Frame
Koki Inoue, Atsushi Koike (Seikei Univ) |
In recent years, research on image processing using deep learning has been active, and an image coding method using neur... [more] |
AIT2023-131
pp.27-30 |
| MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-21
13:00 |
Hokkaido |
Hokkaido Univ. |
Fast designing method of additional patterns in self-referential holographic data storage
-- Approach using deep neural network --
Kazuki Chijiwa, Masanori Takabayashi (Kyushu Inst. of Tech.) |
In self-referential holographic data storage (SR-HDS) known as a purely one-beam holographic recording method, it has be... [more] |
MMS2023-7 ME2023-27 AIT2023-7
pp.35-40 |
| MMS, ME, AIT, IEICE-IE, IEICE-ITS [detail] |
2023-02-22
13:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Age Estimation of Chum Salmon based on Characteristics of Annulus
Mikiyasu Nishiyama, Genki Suzuki, Hiroyuki Shioya (Muroran IT) |
In Hokkaido, fishing salmon, squid, and other representative regional marine products could be better, and research and ... [more] |
MMS2023-30 ME2023-50 AIT2023-30
pp.231-234 |
| IST |
2022-12-12
14:20 |
Shizuoka |
Sanaru Hall |
[Poster Presentation]
[Poster Presentation] Non-invasive non-contact gingival thickness imaging using visible light and near infrared light
Ryotaro Mori, Keiichiro Kagawa (Shizuoka Univ.), Jun Tanida (Osaka Univ.), Chizuko Ogata (Osaka Dental Univ.) |
Gingival thickness is important information in periodontal surgery and gingival recession. In this study, we propose a n... [more] |
IST2022-56
pp.47-48 |
| 3DMT |
2022-10-17
15:40 |
Tochigi |
(Primary: On-site, Secondary: Online) |
Blurring correction using super-resolution on convolutional neural Network for aerial image with dihedral corner reflector array
Takumi Nagao, Daisuke Miyazaki (Osaka Metropolitan Univ.) |
Aerial images with dihedral corner reflector array have the advantages that they do not have image aberration and restri... [more] |
3DMT2022-47
pp.29-32 |
| BCT, IEICE-SIS |
2022-10-13
16:00 |
Aomori |
Hachinohe Institute of Technology
(Primary: On-site, Secondary: Online) |
[Invited Talk]
Quasiconformal Mapping and its Application
-- Numerical Method and Application to Machine Learning --
Hirokazu Shimauchi (Hachinohe Inst. of Tech.) |
Quasiconformal mapping is a natural generalization of conformal mapping and plays an important role in the areas of math... [more] |
|
| IST |
2022-09-22
16:20 |
Tokyo |
Kikai-Shinko-Kaikan Bldg.
(Primary: On-site, Secondary: Online) |
Image Classification Using Neural Network for Feature Extractable CMOS Image Sensor
Kohei Yamamoto, Kota Yoshida, Shunsuke Okura (Ritsumei Univ) |
CMOS image sensors are expected to be integrated with AI using deep learning for new technologies. Our research group ha... [more] |
IST2022-39
pp.21-24 |
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-20
16:40 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
3D Medical Image Segmentation Using 2.5D Deformable Convolutional CNN
Yuya Okumura, Kudo Hiroyuki, Takizawa Hotaka (Tsukuba Univ.) |
An effective method to improve the accuracy of 3D medical image segmentation using deep learning is to use deformable co... [more] |
|
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-20
17:00 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
Deformable registration of 3D medical images with Deep Residual UNet
Taiga Nakamura, Yuki Sato, Hiroyuki Kudo, Hotaka Takizawa (Univ. of Tsukuba) |
(To be available after the conference date) [more] |
|
| AIT, IIEEJ, AS, CG-ARTS |
2022-03-08
10:30 |
Online |
Online |
Towards the 3D reconstruction from illustration images
Shen Qian, Itoh Takayuki (Ocha Univ.) |
This paper presents our trial of 3D model reconstruction from illustration images. Recovery of the depth information i... [more] |
AIT2022-100
pp.243-245 |
| HI, IEICE-HIP, ASJ-H, VRPSY [detail] |
2022-02-27
14:15 |
Online |
on line |
A time-series learning model for estimating the microsaccade segments from fixation eye movement data
Tomoaki Morimoto, Kousuke Nakagaki, Masahito Sakaguchi, Ryoma Kobata, Hisashi Yoshida, Takeshi Kohama (Kindai Univ.) |
In this study, we constructed a time-series learning model with the structure of Bi-LSTM for fixation eye movement data ... [more] |
HI2022-4
pp.33-38 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
13:15 |
Online |
online |
Towards Universal Deep Image Compression
Koki Tsubota (UTokyo), Hiroaki Akutsu (Hitachi), Kiyoharu Aizawa (UTokyo) |
In this paper, we investigate deep image compression towards universal usage. In image compression, it is desirable to b... [more] |
|