Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa |
Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Analyzing and Recognizing Synergetic Functions between Head Movements and Facial Expressions in Conversations Mai Imamura, Kazuki Takeda (YNU), Shiro Kumano (NTT), Kazuhiro Otsuka (YNU) |
In this paper, we propose machine-learning models for recognizing the synergetic functions between facial expressions an... [more] |
|
MBE, NC |
2022-12-03 11:00 |
Osaka |
Osaka Electro-Communication University |
Image Classification Using Gabor Filters as Preprocessing for CNNs Akito Morita, Hirotsugu Okuno (OIT) MBE2022-32 NC2022-54 |
Image preprocessing is a promising approach to improve accuracy in image classification using convolutional neural netwo... [more] |
MBE2022-32 NC2022-54 pp.43-46 |
PRMU |
2022-10-21 15:25 |
Tokyo |
Miraikan - The National Museum of Emerging Science and Innovation (Primary: On-site, Secondary: Online) |
Features and Deep Learning Models Suitable for Speech Source Discrimination Method in Plural Voice User Interfaces Environment Kengo Maeda, Takahiro Yoshida (TUS) PRMU2022-27 |
Under the situation that plural devices equipped with a voice user interface exist in the user’s environment in the near... [more] |
PRMU2022-27 pp.29-34 |
EMCJ, MW, EST, IEE-EMC [detail] |
2022-10-13 09:05 |
Akita |
Akita University (Primary: On-site, Secondary: Online) |
An estimation of magnetic coupling coefficient between parallel two MSLs using machine leaning of near field information Yusuke Sato, Sho Muroga, Hidefumi Kamozawa, Motoshi Tanaka (Akita Univ.) EMCJ2022-35 MW2022-81 EST2022-45 |
An estimation method of the magnetic coupling coefficient between printed-circuit-board-level lines using a near field i... [more] |
EMCJ2022-35 MW2022-81 EST2022-45 pp.1-5 |
BioX |
2022-10-03 13:30 |
Okinawa |
|
Performance Improvement of CNN-Based Fingerprint Recognition Using Multiple Attention Mechanism Nagisa Sasuga, Koichi Ito, Takafumi Aoki (Tohoku Univ.) BioX2022-55 |
Fingerprint recognition methods that extract multiple features from a fingerprint image using a Convolutional Neural Net... [more] |
BioX2022-55 pp.1-6 |
BioX |
2022-10-03 14:30 |
Okinawa |
|
A Study of Region-Based Iris Recognition Using Convolutional Neural Network Shokei Kawakami, Hiroya Kawai, Koichi Ito, Takafumi Aoki (Tohoku Univ.), Yoshiko Yasumura, Masakazu Fujio, Yosuke Kaga, Kenta Takahashi (Hitachi) BioX2022-57 |
The iris, the ring-shaped area between the pupil and the sclera of the eye, has a unique pattern that can be used to ide... [more] |
BioX2022-57 pp.13-18 |
US |
2022-09-20 13:50 |
Online |
Online |
Basic study of optimal training data creation conditions for computer-aided diagnosis using ultrasound images of breast tumors Makoto Yamakawa (SIT), Miho Kanda, Moe Ohshima (Kyoto Univ.), Takeshi Namita, Tsuyoshi Shiina (SIT) US2022-39 |
The quality of training data is important in the development of computer-aided diagnosis (CAD) that automatically detect... [more] |
US2022-39 pp.10-13 |
AI |
2022-09-16 15:45 |
Shizuoka |
(Primary: On-site, Secondary: Online) |
An image restoration method for lecture videos with projected lecture slides Yuma Ito, Masato Kikuchi, Tadachika Ozono (NIT) AI2022-32 |
The lecturers can use their body movements and gestures in the lectures with slides displayed using a projector in the r... [more] |
AI2022-32 pp.79-84 |
PRMU |
2022-09-14 16:00 |
Kanagawa |
(Primary: On-site, Secondary: Online) |
Convolutional Skip Connection for Compressing DNNs with Branched Architectures Koji Kamma, Toshikazu Wada (Wakayama Univ.) PRMU2022-16 |
Although Deep Neural Network (DNN) is a core technology in Computer Vision, it is difficult to implement DNN models beca... [more] |
PRMU2022-16 pp.37-42 |
RECONF |
2022-09-08 10:10 |
Aichi |
emCAMPUS STUDIO (Primary: On-site, Secondary: Online) |
Proposal and evaluation of Combined Posit MAC unit (CPMAC) for both DNN inference and training Yuta Masuda, Yasuhiro Nakahara, Masato Kiyama, Masahiro Iida (Kumamoto Univ.) RECONF2022-34 |
Recently, there has been a lot of research on DNN hardware accelerators for the edge that use Posit as a number represen... [more] |
RECONF2022-34 pp.29-34 |
SIP |
2022-08-25 14:33 |
Okinawa |
Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Structured Deep Image Prior with Interscale Thresholding Jikai Li, Shogo Muramatsu (Niigata Univ.) SIP2022-55 |
This work proposes a novel image denoising technique inspired by the deep image prior (DIP) method. Our contribution is ... [more] |
SIP2022-55 pp.31-36 |
SAT, RCS (Joint) |
2022-08-26 11:40 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Inter-cell Interference Control by Joint Transmit Power and Transmit Beamforming Control based on Machine Learning Naoto Tamada, Yuyuan Chang, Kazuhiko Fukawa (Tokyo Tech) RCS2022-118 |
In mobile communications, densely deployed small cell systems using the same frequency band are expected to increase the... [more] |
RCS2022-118 pp.120-125 |
ICD, SDM, ITE-IST [detail] |
2022-08-10 16:00 |
Online |
|
IC with Integrated Imager and Ultra-Low Latency All-Digital In-Imager 2D Binary Convolutional Neural Network Accelerator for Image Classification Ruizhi Wang, Cheng-Hsuan Wu, Makoto Takamiya (The Univ. of Tokyo) SDM2022-53 ICD2022-21 |
In the field of real-time image recognition, the computing latency of convolutional neural network become an issue. In t... [more] |
SDM2022-53 ICD2022-21 pp.87-92 |
NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-14 14:30 |
Ishikawa |
The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
IRS placement method for improving radio environment spaces shielded by structures Kazuki Fujii, Katsuya Suto (UEC) SR2022-31 |
Due to the linearity of radio waves used in Beyond 5G systems, users may suffer from outages even near a base station. T... [more] |
SR2022-31 pp.54-60 |
CCS, NLP |
2022-06-09 14:15 |
Osaka |
(Primary: On-site, Secondary: Online) |
Improvement of Recognition Accuracy by Sequential Execution of Unsupervised Learning and Semi-supervised Learning Hiroki Murakami, Hidehiro Nakano (Tokyo City Univ.) NLP2022-4 CCS2022-4 |
In this study, we propose a sequential learning method that improves recognition accuracy by alternately utilizing the k... [more] |
NLP2022-4 CCS2022-4 pp.17-22 |
CCS, NLP |
2022-06-09 14:55 |
Osaka |
(Primary: On-site, Secondary: Online) |
Basic Performance of CNNs Using Dynamic Filters Based on Octave Convolution Kiyotaka Matono, Hidehiro Nakano (Tokyo City Univ.) NLP2022-5 CCS2022-5 |
The methods of using dynamic filters for convolutional neural networks (CNNs) have attracted attentions. In recent years... [more] |
NLP2022-5 CCS2022-5 pp.23-26 |
RECONF |
2022-06-08 15:25 |
Ibaraki |
CCS, Univ. of Tsukuba (Primary: On-site, Secondary: Online) |
A Compact High-Speed CNN Implementation based on Redundant Computational Analysis and FPGA Acceleration Li Qi, Li Hengyi, Meng Lin (Ritsumeikan Univ.) RECONF2022-21 |
Convolutional Neural Networks (CNNs) have achieved high performance and are widely used in various applications. However... [more] |
RECONF2022-21 pp.89-94 |
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] |
2022-05-20 16:40 |
Kumamoto |
Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
3D Medical Image Segmentation Using 2.5D Deformable Convolutional CNN Yuya Okumura, Kudo Hiroyuki, Takizawa Hotaka (Tsukuba Univ.) SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 |
An effective method to improve the accuracy of 3D medical image segmentation using deep learning is to use deformable co... [more] |
SIP2022-29 BioX2022-29 IE2022-29 MI2022-29 pp.150-155 |
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] |
2022-05-20 17:00 |
Kumamoto |
Kumamoto University Kurokami Campus (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) SIP2022-30 BioX2022-30 IE2022-30 MI2022-30 |
(To be available after the conference date) [more] |
SIP2022-30 BioX2022-30 IE2022-30 MI2022-30 pp.156-160 |
IT, EMM |
2022-05-17 15:30 |
Gifu |
Gifu University (Primary: On-site, Secondary: Online) |
A study of adversarial example detection using the correlation between adversarial noise and JPEG compression-derived distortion Kenta Tsunomori, Yuma Yamasaki, Minoru Kuribayashi, Nobuo Funabiki (Okayama Univ.), Isao Echizen (NII) IT2022-6 EMM2022-6 |
Adversarial examples cause misclassification of image classifiers. Higashi et al. proposed a method to detect adversari... [more] |
IT2022-6 EMM2022-6 pp.29-34 |