| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| 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 |
| 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 |
| BCT, IEEE-BT |
2021-09-03
13:35 |
Online |
Online |
Convolutional Radio Modulation Recognition Networks with Attention Models in Wireless Systems
Haohui Jia, Na Chen, Minoru Okada (NAIST) |
In modern wireless systems, deep learning (DL) shows promising performance for wireless signal processing. DL model driv... [more] |
BCT2021-35
pp.1-4 |
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-18
13:50 |
Online |
Online |
Detecting axillary lymph node metastasis of breast cancer with FDG-PET/CT images based on attention mechanism
Zongyao Li, Ren Togo, Kenji Hirata (Hokkaido Univ.), Kazuhiro Kitajima (Hyogo Med.), Junki Takenaka (Hokkaido Univ.), Yasuo Miyoshi (Hyogo Med.), Kohsuke Kudo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Determination of axillary nodal status is significant to treatment of breast cancer. Typically, the diagnosis of axillar... [more] |
MMS2021-7 ME2021-7 AIT2021-7
pp.33-36 |
| 3DMT, IEICE-SIS, IPSJ-AVM [detail] |
2020-06-04
14:00 |
Online |
G Square (Hakodate Community Plaza) |
An experimental comparison of CNN- and CRNN-CTC for automatic phrase speech recognition systems using a children's speech database
Yunzhe Wang, Yu Tian (Hokkaido Univ.), Yoshikazu Miyanaga (CIST), Hiroshi Tsutsui (Hokkaido Univ.) |
Children's speech recognition is still a challenging issue. In the case of children's speeches, the accuracy of conventi... [more] |
|
| IEICE-MI, IEICE-IE, IEICE-SIP, IEICE-BioX, IST, ME [detail] |
2020-05-28
10:50 |
Online |
Online |
[Special Talk]
High-dimensional Signal Restoration by Convolutional Networks Driving Fusion Across Multiple Disciplines
-- Sparse Modeling and Convolutional Dictionary Learning --
Shogo Muramatsu (Niigata Univ.) |
This talk outlines a restoration process of high-dimensional signals such as image and volumetric data. With the develop... [more] |
IST2020-30 ME2020-81
p.13 |
| AIT, IIEEJ, AS, CG-ARTS |
2019-03-12
15:45 |
Tokyo |
Waseda Univ. |
Semantic Segmentation for 3D Human Models
Satoshi Yamaguchi, Yoshihiro Kanamori, Jun Mitani (University of Tsukuba) |
We propose a technique for semantic segmentation of 3D human models. Existing techniques for general 3D objects solely r... [more] |
AIT2019-80
pp.119-122 |
| ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] |
2019-02-20
13:30 |
Hokkaido |
Hokkaido Univ. |
Evaluation of Multi-level Data Demodulation Using Convolutional Neural Networks for Holographic Data Storage
Yutaro Katano, Tetsuhiko Muroi, Nobuhiro Kinoshita, Norihiko Ishii (NHK) |
Holographic data storage (HDS) is a promising next generation archival memory with large capacity, high data-transfer ra... [more] |
MMS2019-20 HI2019-20 ME2019-42 AIT2019-20
pp.205-208 |
| ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] |
2019-02-20
16:15 |
Hokkaido |
Hokkaido Univ. |
[Invited Talk]
Automatic Gaze Correction based on Deep Learning and Image Warping
Masataka Seo, Yamamoto Takahiro (Ritsumeikan Univ), Toshihiro Kitajima (Samsung), Chen Yen-Wei (Ritsumeikan Univ) |
When people take a selfie photo or talk through a video chat system, they tend to look at the screen. Since the position... [more] |
MMS2019-25 HI2019-25 ME2019-47 AIT2019-25
pp.255-259 |
| IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-16
13:15 |
Hokkaido |
Hokkaido Univ. |
Suppression of Inter-symbol Interference by Convolutional Neural Networks for Holographic Data Storage
Yutaro Katano, Tetsuhiko Muroi, Kinoshita Nobuhiro, Norihiko Ishii (NHK) |
Holographic data storage (HDS) is a promising for next generation archival media. In reproduction, reproduced data of tw... [more] |
MMS2018-25 HI2018-25 ME2018-25 AIT2018-25
pp.267-270 |