| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| ME |
2022-07-22
16:50 |
Online |
Online |
Deep Learning based Compressed Sensing Image Reconstruction Using Multiple Signal Under-sampling Pattern
Masaki Shibui, Kazuki Yamato, Satoshi Ito (Utsunomiya Univ.) |
CS-MRI, which is an application of compressed sensing (CS) to MR image acquisition, can reconstruct MR images from a sma... [more] |
ME2022-71
pp.27-29 |
| IEICE-SIP, IEICE-BioX, IEICE-IE, IEICE-MI, IST, ME [detail] |
2022-05-19
16:10 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
[Invited Talk]
Image and Video Restoration with Deep Learning
Satoshi Iizuka (Univ. of Tsukuba) |
In this talk, I will introduce techniques for restoring black-and-white images and videos with high accuracy using deep ... [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
16:20 |
Kumamoto |
Kumamoto University
(Primary: On-site, Secondary: Online) |
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis
Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) |
It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly ... [more] |
|
| 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
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
10:30 |
Online |
Online |
Using Deep Learning to Generate Water Effects for 2D Animation
Zhaolou Liang, Masaki Abe, Taichi Watanabe (Tokyo Univ of Technology) |
In 2D animation effects, hand-drawn drawings and 3D simulations are used. Hand-drawn images have a high artistic and des... [more] |
AIT2022-112
pp.283-284 |
| 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] |
2022-02-28
09:45 |
Online |
on line |
Estimation of speech emotional intensity model using impression ratings
Megumi Kawase, Minoru Nakayama (Tokyo Tech) |
We used deep learning to estimate emotional intensity from speech. In our previous study, we considered emotional intens... [more] |
|
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
16:45 |
Online |
online |
A Note on Disentanglement Using Deep Generative Model Based on Variational Autoencoder
-- Introduction of Regularization Losses Based on Metrics of Disentangled Representation --
Nao Nakagawa, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we study disentangled representation learning using a deep generative model based on Variational Autoenco... [more] |
MMS2022-19 ME2022-44 AIT2022-19
pp.97-102 |
| 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
12:45 |
Online |
online |
Regularizing Generative Adversarial Networks with Internal Representation of Generators
Yusuke Hara, Toshihiko Yamasaki (UTokyo) |
In training generative adversarial networks, maintaining the criteria of the discriminator stably is crucial to training... [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
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
14:40 |
Online |
online |
A Study on Object Detection in Omnidirectional Images Using Deep Learning
Yasuyuki Ishida, Toshio Ito (SIT) |
A minimum sensor configuration is desired for a popular automatic vehicle. In this study, an omnidirectional camera with... [more] |
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