| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-19
15:10 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
Arrhythmia catheter ablation point prediction from ECG and CT image based on machine learning
Kazuyuki Ohmura (GEHCJ), Kenichiro Yamagata, Kengo Kusano (NCVC), Nozomu Uetake (GEHCJ) |
Catheter ablation is the key therapy in treating arrhythmia. For this treatment planning, 3D electroanatomical map is us... [more] |
|
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-20
09:40 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
User identification on Walking by Deep Learning Based on 3-axis Acceleration after Coordinate Transformation of Smartphone
Pengfei Yang, Qun Yang, Yuji Watanabe (Nagoya City Univ.) |
In this paper, we first transform the 3-axis acceleration data of smart phone, which is left in our laboratory, from the... [more] |
|
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-20
11:30 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
Implementation of a Lightweight Automatic Speech Recognition System at the Edge
Haotian Tan, Junichi Akita (Kanazawa Univ.) |
Automatic speech recognition (ASR) on the cloud has been widely adopted and has demonstrated satisfactory performance. W... [more] |
IST2022-23 ME2022-63
pp.111-114 |
| 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] |
|
| AIT, IIEEJ, AS, CG-ARTS |
2022-03-08
13:16 |
Online |
Online |
Semi-automatic Manga Colorization Using Flat Colored Images
Yugo Shimizu (TUS), Ryosuke Furuta (UTokyo), Delong Ouyang, Yukinobu Taniguchi (TUS), Ryota Hinami, Shonosuke Ishiwatari (Mantra) |
To create color comics, manual colorization process is required, which incurs high labor costs. To solve the problem, we... [more] |
AIT2022-67
pp.115-118 |
| AIT, IIEEJ, AS, CG-ARTS |
2022-03-08
13:28 |
Online |
Online |
Style-invariant representations and frame-aware constraints for manga face image clustering
Shunta Komatsu (TUS), Ryosuke Furuta (UTokyo), Yukinobu Taniguchi (TUS), Ryota Hinami, Shonosuke Ishiwatari (Mantra) |
Character recognition in manga is an important task to improve the usability of e-comics through recommendation systems ... [more] |
AIT2022-78
pp.153-156 |
| AIT, IIEEJ, AS, CG-ARTS |
2022-03-08
13:50 |
Online |
Online |
An Experimental Study on Estimating Residual Quantity of Foodstuff based on Deep Learning using 3D Model
Hiromu Takata, Syuhei Sato, Shangce Gao, Zheng Tang (Univ. Of Toyama) |
With the recent development of deep learning techniques, many image recognition methods have been proposed for various o... [more] |
AIT2022-147
pp.393-394 |
| 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
12:45 |
Online |
online |
Quality Assessment for 3D CG Image Colorization Using Visible Digital Watermarking after Noise Removal Based on Sparse Dictionary Learning Coding
Norifumi Kawabata (Hokkaido Univ.) |
Thus far, we discussed to represent image data whether it is possible or not to represent meaning image how requirement ... [more] |
MMS2022-6 ME2022-31 AIT2022-6
pp.31-36 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
13:30 |
Online |
online |
A Note on Automatic Diagnosis of Helicobacter Pylori Infection Based on Self-Supervised Learning and Self-Knowledge Distillation
Guang Li, Ren Togo (Hokkaido Univ.), Katsuhiro Mabe (Junpukai Health Maintenance Center), Shunpei Nishida (Olympus), Yoshihiro Tomoda (Olympus Medical Systems), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper proposes a novel method for automatic diagnosis of Helicobacter pylori (H. pylori) infection based on self-su... [more] |
MMS2022-9 ME2022-34 AIT2022-9
pp.49-52 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
11:00 |
Online |
online |
Illustration author style translation using SailormoonRedraw data
Keita Awane, Daichi Horita, Hikaru Ikuta, Yusuke Matsui (UTokyo), Naohiro Yanase (BOOK WALKER), Kiyoharu Aizawa (UTokyo) |
The author characteristics of illustrations can be divided into two elements: "what to draw" and "how to draw". The latt... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
11:30 |
Online |
online |
|
The dynamic range of electronic imaging is orders of magnitudes smaller than that of human vision. To obtain images of h... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
13:00 |
Online |
online |
Domain Incremental Leaning with Adaptive Loss Functions
Takumi Kawashima (UTokyo), Go Irie, Daiki Ikami (NTT), Kiyoharu Aizawa (UTokyo) |
During domain incremental learning of image classification task, the distribution of images continually change, and mode... [more] |
|
| 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] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
14:25 |
Online |
online |
A Note on Visual Sentiment Prediction Based on Few-shot Learning using Knowledge Distillation
Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
The prediction of visual sentiment can be useful to understand users' behaviors. Emotion theories underlying the sentime... [more] |
MMS2022-24 ME2022-49 AIT2022-24
pp.171-175 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
15:05 |
Online |
online |
A Note on Personalized Saliency Prediction Based on User Similarity Considering Object Information in Images
Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a personalized saliency map (PSM) prediction method using a small amount of gaze data based on user ... [more] |
MMS2022-26 ME2022-51 AIT2022-26
pp.181-186 |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
15:35 |
Online |
online |
Liver Tumor Segmentation by Using a Massive-Training Artificial Neural Network (MTANN) and its Analysis in Liver CT.
Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki (Tokyo Tech) |
Based on a 3D massive-training artificial neural network (MTANN) combined with a Hessian-based ellipse enhancer, a small... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
10:15 |
Online |
online |
Classification of User's Device Possession Position and Behavior by Using Deep Metric Learning
Rui Kitahara, Lifeng Zhang (Kyutech) |
With the widespread use of smartphones, there have been efforts to classify human behavior using built-in sensors. Howev... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
10:15 |
Online |
online |
Contrastive Self-Supervised Learning Framework for Unsupervised Video Summarization
Xianliang Zhang, Li Tao (UTokyo), Xueting Wang (CyberAgent AI Lab), Toshihiko Yamasaki (UTokyo) |
The rapid growth of video data aggravates the effort by viewers in exploring informative data. This paper presents a fra... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-22
10:45 |
Online |
online |
|
There has been a tremendous progress in unsupervised domain adaptation (UDA), which aims to transfer knowledge acquired ... [more] |
|