| Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
| AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] |
2022-02-21
16:15 |
Online |
online |
A Note on Realizing Adversarial Defense Based on Regularization of Multi-stage Squeeze-and-Excitation Features
Jiahuan Zhang, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Regularizing deep features is a common adversarial defense method. However, the existing methods do not further explore ... [more] |
MMS2022-17 ME2022-42 AIT2022-17
pp.87-90 |
| 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
15:20 |
Online |
online |
A Note on Electron Microscope Image Generation from Mix Proportion and Material Property via Generative Adversarial Network for Rubber Materials
Rintaro Yanagi, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Estimating the properties of rubber materials from ingredients is necessary to accelerate rubber material development. A... [more] |
MMS2022-27 ME2022-52 AIT2022-27
pp.187-191 |
| ME |
2021-12-13
14:50 |
Online |
online |
Latent expression separation using the locality of changes in the real image
Toshiki Hazama (Ritsumeikan Univ.), Masataka Seo (OIT), Yen-Wei Chen (Ritsumeikan Univ.) |
GAN, a deep generative model, makes a great contribution to the image generation task. However, one of the problems that... [more] |
ME2021-95
pp.29-31 |
| ME |
2021-12-13
15:20 |
Online |
online |
Automatic Generation of Viewpoint Change Video Using Consistent Regularized Generative Adversarial Networks
Kento Otsu (Ritsumeikan Univ.), Masataka Seo (Osaka Institute of Technology Osaka), Yen-Wei Chen (Ritsumeikan Univ.) |
Gaze plays an important role in conversation. However, in a video call system using a personal computer or the like, it ... [more] |
ME2021-96
pp.33-35 |
| BCT, IEICE-SIS |
2021-10-07
14:25 |
Online |
online |
Block-wise Transformation with Secret Key for Adversary Robust Defence of SVM model
Ryota Iijima, MaungMaung AprilPyone, Hitoshi Kiya (TMU) |
In this paper, we propose a method for implementing support vector machine (SVM) models that are robust against adversar... [more] |
|
| BCT, IEICE-SIS |
2021-10-08
11:30 |
Online |
online |
Analysis of Writing Style on Wood Slips of the Chinese Han period Using Deep Generative Model
Chiang Meng Yuan, Soh Yoshida, Takao Fujita, Mitsuji Muneyasu (Kansai Univ.) |
In this paper, we develop a method to objectively analyze the calligraphic styles of wood slips excavated in Northwester... [more] |
|
| IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2021-02-19
14:15 |
Online |
Online |
[Special Talk]
A Note on Electron Microscope Image Generation from Mix Proportion via Conditional Style Generative Adversarial Network for Rubber Materials
Rintaro Yanagi, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
Estimating the properties of rubber materials from ingredients is necessary to accelerate rubber material development. I... [more] |
MMS2021-22 ME2021-22 AIT2021-22
pp.171-175 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
16:20 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
A Note on Generation of Electron Microscope Images via Auxiliary Classifier Generative Adversarial Network with Mix Proportions
Misaki Kanai, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
In this paper, we investigate a method for generation of images that represent the internal structure of rubber material... [more] |
MMS2020-21 HI2020-21 ME2020-49 AIT2020-21
pp.107-111 |
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-27
14:00 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
An Image Transformation Network for Privacy-Preserving Deep Neural Networks
Hiroki Ito, Yuma Kinoshita, Hitoshi Kiya (Tokyo Metro. Univ.) |
We propose an image transformation network to generate visually-protected images for privacy-preserving deep neural netw... [more] |
|
| HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] |
2020-02-28
15:10 |
Hokkaido |
Hokkaido Univ.
(Cancelled) |
Unpaired Learning for Noise-free, Scale Invariant, and Interpretable Image Enhancement
Satoshi Kosugi, Toshihiko Yamasaki (Univ. of Tokyo) |
This paper tackles unpaired image enhancement, a task of learning a mapping function which transforms input images into ... [more] |
|
| BCT, IEEE-BT |
2020-02-20
13:45 |
Shiga |
|
Evaluation of 429MHz band multiple folded Planar Inverted F Antenna near human body
Kanata Muto, Katsuyuki Fujii, Yasuyuki Okumura (Nanzan Univ.) |
It has been reported that the characteristics of an antenna built into a mobile communication terminal that is expected ... [more] |
BCT2020-23
pp.9-12 |
| IEICE-IE, IEICE-CS, IPSJ-AVM, BCT [detail] |
2019-12-06
10:10 |
Iwate |
Aiina Center |
Adversarial Examples for Monocular Depth Estimation CNN
Koichiro Yamanaka, Ryutaroh Matsumoto, Keita Takahashi, Toshiaki Fujii (Nagoya Univ.) |
Adversarial examples for classification and object recognition problems using convolutional neural net- works (CNN) have... [more] |
|
| BCT, IEEE-BT |
2019-02-21
13:15 |
Shizuoka |
Kanponoyado Yaizu |
SAR Evaluations in the head close to wireless LAN router with multiple antennas
Kosuke Nishino, Kazuyuki Saito (Chiba Univ.), Tomoaki Nagaoka, Soichi Watanabe (NICT), Masaharu Takahashi (Chiba Univ.) |
Along with the remarkable information conversion in recent years, the spread of wireless communication devices has progr... [more] |
BCT2019-23
pp.1-4 |
| BCT, IEEE-BT |
2019-02-21
13:35 |
Shizuoka |
Kanponoyado Yaizu |
Evaluation of SAR and reflection coefficient based on the position between folded dipole antenna and a planar reflector at 1.2 GHz band
Yu Kumita, Katsuyuki Fujii, Yasuyuki Okumura (Nanzan Univ.) |
The antennas builted in the mobile communication terminal are used near the human body. The presence of the human body c... [more] |
BCT2019-24
pp.5-8 |
| BCT, IEEE-BT |
2019-02-21
13:55 |
Shizuoka |
Kanponoyado Yaizu |
Electromagnetic Field Distribution and SAR Evaluation of 2.4 GHz Band 2-D Communication Sheet near the Human Body
Ibuki Uda, Katsuyuki Fujii, Yasuyuki Okumura (Nanzan Univ.) |
As an application of a medium which can communicate and transmit power called a 2-D Communication Sheet, studies have be... [more] |
BCT2019-25
pp.9-12 |
| BCT, IEEE-BT |
2018-02-22
15:25 |
Toyama |
Kanponoyado-Toyama |
Proposal of a simplified electromagnetic field analysis model and SAR evaluation for a motorcycle equipped with a whip antenna
Ryusuke Kato, Katsuyuki Fujii, Yasuyuki Okumura (Nanzan Univ.) |
In this study, we describe the design guidelines for a whip antenna equipped on a motorcycle while considering the influ... [more] |
BCT2018-29
pp.21-24 |
| IEICE-ITS, IEICE-IE, MMS, HI, ME, AIT [detail] |
2018-02-16
10:45 |
Hokkaido |
Hokkaido Univ. |
A Note on Use of Generative Adversarial Networks for Gastritis Classification from Gastric X-ray Images
Ren Togo, Kenta Ishihara, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents potential of gastritis images generated by generative adversarial networks (GANs) for gastritis clas... [more] |
MMS2018-31 HI2018-31 ME2018-31 AIT2018-31
pp.299-303 |
| BCT, IEEE-BT [detail] |
2017-02-23
14:45 |
Aichi |
Kanpo-no-yado Chita-mihama |
SAR evaluations for human bodies due to voice communications and data communications using a smartphone
Ryota Takei, Kosuke Nishino (Chiba Univ.), Tomoaki Nagaoka (NICT), Kazuyuki Saito (Chiba Univ.), Soichi Watanabe (NICT), Masaharu Takahashi (Chiba Univ.) |
Today, novel mobile phones such as a smartphone and a tablet computer have been spreading tremendously. We have more sit... [more] |
BCT2017-27
pp.17-20 |
| IST |
2016-11-17
16:30 |
Tokyo |
TITECH Tamachi Campus |
[Poster Presentation]
A High-speed Low-power CMOS Image Sensor with Delta and Interpolation Readout Scheme
Hyeon-June Kim, Sun-Il Hwang, Seung-Tak Ryu (KAIST) |
This paper presents a high-speed low-power readout scheme for CMOS image sensors (CISs) that utilizes the image properti... [more] |
IST2016-67
pp.39-40 |