| 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 |
| 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 |
| 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 |
| 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 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
15:20 |
Online |
online |
A Note on Perceived Visual Content Estimation Based on Compressed Reconstruction Network Using Brain Signals While Gazing on Images
Takaaki Higashi, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido University) |
In this paper, we propose a method to reconstruct a perceived image using brain signals obtained during gazing images. S... [more] |
MMS2022-28 ME2022-53 AIT2022-28
pp.349-353 |
| 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 |
| BCT, IEEE-BT |
2022-02-17
13:20 |
Online |
TBD |
Channel Estimation to Mitigate Channel Aging in Massive MIMO with Pilot Contamination
Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.) |
In a massive multiple-input mltiple-output (MIMO) system based on time division duplex (TDD), the channel state informat... [more] |
BCT2021-12
pp.13-16 |
| 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 |
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-18
14:50 |
Online |
Online |
Production and Evaluation of Data Set for Semantic Segmentation of 3D CG Image by H.265/HEVC
Norifumi Kawabata (Tokyo Univ. of Science) |
As one of purpose of study on image segmentation, we are able to consider whether between object and background region c... [more] |
|
| 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 |
| IEICE-MI, IEICE-IE, IEICE-SIP, IEICE-BioX, IST, ME [detail] |
2020-05-29
14:30 |
Online |
Online |
A method for analyze causes of deterioration of predict quality when Deep Learning is applied to instance segmentation
Tomonori Kubota, Takanori Nakao, Masafumi Katoh, Eiji Yoshida, Hidenobu Miyoshi (Fujitsu Lab.) |
In this paper, we propose a method to analyze the cause of deterioration of prediction accuracy in instance segmentation... [more] |
|
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
16:35 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
A Study on Region Segmentation of Color Laparoscopic Images after Contrast Enhancement Including Super-Resolution CNN by Image Regions
Norifumi Kawabata (Tokyo Univ. of Science), Toshiya Nakaguchi (Chiba Univ.) |
As one of image pre-processing method to detect, recognize, and estimate lesion or characteristic region in medical imag... [more] |
MMS2020-22 HI2020-22 ME2020-50 AIT2020-22
pp.113-118 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
13:00 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
Video Coding Using Optimal Intra Prediction Mode Estimation by CNN
Ryota Yokoyama, Masahiko Tahara (Waseda Univ.), Heming Sun (Waseda Univ./JST), Masaru Takeuchi (Waseda Univ.), Yasutaka Matsuo (NHK), Jiro Katto (Waseda Univ.) |
These days, efficient video coding is required due to spread of video production and viewing, and high definition video.... [more] |
|
| BCT, IEEE-BT |
2020-02-20
14:15 |
Shiga |
|
Learning-Based Channel Estimation for Massive MIMO with Pilot Contamination and Its Impact of Model Mismatch in Training
Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.) |
In massive multiple-input multiple-output (MIMO), a base station (BS) needs accurate estimation of channel state informa... [more] |
BCT2020-24
pp.13-16 |
| ME |
2020-02-08
14:45 |
Kanagawa |
Kanto Gakuin University |
Convolutional Neural Network-based bird detection and species recognition from images automatically captured in real environment
Tiankuang Li, Hiroki Kuroda, Wataru Kitamura, Koji Iwano (Tokyo City Univ.) |
Recently, "bird baths" have been installed in various places with the aim of conserving wild birds. In this research, we... [more] |
ME2020-26
pp.89-92 |
| 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 |