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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| DC, SS | 2022-10-25 14:15 |
Fukushima | (Primary: On-site, Secondary: Online) |
Relationship between the Defects in Learning Programs and the Model Distortion on the Convolutional Neural Networks Takumi Tsuchiya, Kozo Okano, Shinpei Ogata (Shinshu Univ.), Shin Nakajima (NII)  SS2022-26 DC2022-32 |
In recent years, the quality issue of machine learning software has become an important concern. When considering the qu... [more] | SS2022-26 DC2022-32 pp.23-28 |
| 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 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 |
| 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 |
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| CS | 2022-07-14 10:20 |
Kagoshima | Yakushima Environmental and Cultural Village Center (Primary: On-site, Secondary: Online) |
User Data Selection using CNN-Feature Extractor for Fingerprint Localization Yohei Konishi, Satoru Aikawa, Shinichiro Yamamoto (Univ of Hyogo) CS2022-10 |
(To be available after the conference date) [more] | CS2022-10 pp.1-2 |
| 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 |
| CCS, NLP | 2022-06-09 15:20 |
Osaka | (Primary: On-site, Secondary: Online) |
Speeding-up by Reduction of Processing Paths in Octave Convolution Akito Yoshikawa, Hidehiro Nakano (Tokyo City Univ.) NLP2022-6 CCS2022-6 |
Octave Convolution (OctConv), one of the convolutional neural network methods, can also improve accuracy while reducing ... [more] | NLP2022-6 CCS2022-6 pp.27-30 |
| 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 |
| ITS, IEE-ITS | 2022-03-11 14:40 |
Online | Online | Gaze Estimation for a Driving Simulator Using Machine Learning Takayuki Furukawa, Yuji Matsuki (FIT) ITS2021-70 |
Several studies have been conducted on gaze estimation in driving simulators due to the widespread attention it has attr... [more] | ITS2021-70 pp.38-43 |
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