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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIS | 2023-03-02 11:00 |
Chiba | Chiba Institute of Technology (Primary: On-site, Secondary: Online) |
Blink detection from one-dimensional face signal by using convolutional sparse dictionary learning Souichiro Maruyama, Makoto Nakashizuka (CIT)  SIS2022-40 |
In this report, a blink detection method from average intensities of whole facial videos using convolutional dictionary... [more] | SIS2022-40 pp.1-4 |
| EMM | 2023-01-26 13:35 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Audio zero-watermarking method based on auditory spectral representation Atsuki Ichikawa, Masashi Unoki (JAIST) EMM2022-65 |
Audio zero-watermark technique creates a detection key from watermark and binary pattern generated from features of the ... [more] | EMM2022-65 pp.20-25 |
| EST | 2023-01-26 16:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Estimation of magnetic dipole positions using sparse modeling Tomonori Yanagida, Yuji Ogata, Bunichi Kakinuma, Masayuki Kimishima (Advantest Lab) EST2022-87 |
In recent years, magnetic fields have attracted attention as applications for non-contact, non-destructive measurement o... [more] | EST2022-87 pp.70-73 |
| IT, RCS, SIP | 2023-01-24 16:20 |
Gunma | Maebashi Terrsa (Primary: On-site, Secondary: Online) |
Underdetermined DOA Estimation of Correlated Signals Using Atomic Norm Minimization Soichi Obata, Steven Wandale, Koichi Ichige (Yokohama Nat'l Univ.) IT2022-50 SIP2022-101 RCS2022-229 |
This paper discusses the underdetermined Direction-of-Arrival (DOA) estimation of correlated sources where the number of... [more] | IT2022-50 SIP2022-101 RCS2022-229 pp.120-125 |
| IBISML | 2022-12-22 13:40 |
Kyoto | Kyoto University (Primary: On-site, Secondary: Online) |
IBISML2022-43 |
In recent years, materials science fields have been conducting efficient materials development through informatics-in th... [more] | IBISML2022-43 pp.4-5 |
| SANE | 2022-12-16 11:25 |
Nagasaki | Nagasaki Public Hall (Primary: On-site, Secondary: Online) |
Polarimetric SAR Ship Detection Based on Sparse Reconstruction Error Saliency Jiahao Luo, Junjun Yin (USTB), Jian Yang (THU) SANE2022-79 |
Ship detection is one of the important applications of polarimetric synthetic aperture radar(SAR) images. In this study,... [more] | SANE2022-79 pp.80-84 |
| RCC, ITS, WBS | 2022-12-13 15:40 |
Shiga | Ritsumeikan Univ. BKC (Primary: On-site, Secondary: Online) |
Design of Structured Sparse Controllers for Cyber-Physical Systems Yuta Kawano, Koichi Kobayashi, Yuh Yamashita (Hokkaido Univ.) WBS2022-39 ITS2022-15 RCC2022-39 |
In this paper, we consider the design of controllers for discrete-time linear systems by sparse optimization. Sparse opt... [more] | WBS2022-39 ITS2022-15 RCC2022-39 pp.26-29 |
| MBE, NC | 2022-12-03 10:20 |
Osaka | Osaka Electro-Communication University | ICA with SCAD penalty via DC algorithm Yusuke Endo, Koujin Takeda (Ibaraki Univ.) MBE2022-31 NC2022-53 |
In this work, we propose an improved method of ICA(Independent Component Analysis), which is used for identifying latent... [more] | MBE2022-31 NC2022-53 pp.38-42 |
| EMT, IEE-EMT | 2022-11-19 09:55 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
Finite Element Method for Periodic Structure Waveguides using Parallel Processing Justin Jun Wilkins, Takashi Kuroki, Toshihiko Shibazaki (TMCIT), Teruhiro Kinoshita (TPU) EMT2022-65 |
The Finite element method is often used for an electromagnetic wave analysis. It requires to divide an analysis domain ... [more] | EMT2022-65 pp.117-120 |
| SIS, ITE-BCT | 2022-10-14 11:05 |
Aomori | Hachinohe Institute of Technology (Primary: On-site, Secondary: Online) |
A Study of Blind Estimation for Sparse Channel Yosuke Sugiura, Kaito Shinoda, Nozomiko Yasui, Tetsuya Shimamura (Saitama Univ.) SIS2022-19 |
In this paper, we propose an estimation method for sparse channel without a pilot symbol in wireless communication based... [more] | SIS2022-19 pp.44-48 |
| SANE | 2022-08-18 16:20 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Parallelization of compressive sensing SAR imaging on server and embedded GPU systems Masato Gocho (Mitsubishi Electric), Kazunori Ueda (Waseda Univ.) SANE2022-40 |
CS-SAR (compressive sensing synthetic aperture radar) imaging, in which truncated signals are observed and reconstructed... [more] | SANE2022-40 pp.38-43 |
| ICTSSL | 2022-07-29 13:55 |
Osaka | Kansai University (Primary: On-site, Secondary: Online) |
Behavior Analysis of Evacuees using Sparse Structure Learning for Development of Emergency Rescue Evacuation Support System Yeboon Yun, Tomotaka Wada (Kansai Univ.) ICTSSL2022-13 |
We have developed the Emergency Rescue Evacuation Support System (ERESS) which is designed to automatically detect disas... [more] | ICTSSL2022-13 pp.16-21 |
| EMM, BioX, ISEC, SITE, ICSS, HWS, IPSJ-CSEC, IPSJ-SPT [detail] | 2022-07-20 15:25 |
Online | Online | An Efficient Sparse Multiplication Algorithm For Pairing-Friendly Elliptic Curves With Cubic Twist Daiki Hayashida, Kenichiro Hayasaka (Mitsubishi Electric Corp.), Tadanori Teruya (AIST) ISEC2022-26 SITE2022-30 BioX2022-51 HWS2022-26 ICSS2022-34 EMM2022-34 |
In this paper, we propose an efficient sparse multiplication algorithm on elliptic curves with cubic twist based on the ... [more] | ISEC2022-26 SITE2022-30 BioX2022-51 HWS2022-26 ICSS2022-34 EMM2022-34 pp.110-117 |
| NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-14 15:00 |
Ishikawa | The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
Network Diagnosis with Group Testing
-- Minimum Number of Measurements and Optimal Probes -- Fangyuan Xu, Shun-ichi Azuma, Ryo Ariizumi, Toru Asai (Nagoya Univ.) RCC2022-29 |
In a network system, some connection failures may occur over the links. The administrator has to detect such links as so... [more] | RCC2022-29 pp.54-56 |
| RCS | 2022-06-17 10:05 |
Okinawa | University of the Ryukyus, Senbaru Campus and online (Primary: On-site, Secondary: Online) |
A Study on Irregular Sparse Superposition Code for Massive NOMA Detection Shinya Oishi, Shinsuke Ibi (Doshisha Univ.), Takumi Takahashi (Osaka Univ.), Hisato Iwai (Doshisha Univ.) RCS2022-58 |
Orthogonal multiple access (OMA) is finding it difficult to cope with the increase in wireless traffic due to the Intern... [more] | RCS2022-58 pp.200-205 |
| RECONF | 2022-06-07 16:35 |
Ibaraki | CCS, Univ. of Tsukuba (Primary: On-site, Secondary: Online) |
Design of a Quantum Annealing Accelerator for Sparse Ising Model Yuta Ohma, Hasitha Muthumala Waidyasooriya, Masanori Hariyama (Tohoku Univ.) RECONF2022-10 |
(To be available after the conference date) [more] | RECONF2022-10 pp.45-47 |
| MSS, NLP | 2022-03-29 09:40 |
Online | Online | Effects of sparse connections in spiking neural networks for unsupervised pattern recognition Hiroki Shinagawa, Kantaro Fujiwara, Gouhei Tanaka (Univ. of Tokyo) MSS2021-69 NLP2021-140 |
Recently, the spiking neural network (SNN) models, which compute using spatio-temporal information representation by neu... [more] | MSS2021-69 NLP2021-140 pp.71-76 |
| MBE, NC (Joint) |
2022-03-02 11:00 |
Online | Online | Learning of a stacked autoencoder with regularizers added to the cost function, evaluation of their effectiveness, and clarification of its information compression mechanism Masumi Ishikawa (Kyutech) NC2021-49 |
Deep learning has a serious drawback in that the resulting models tend to be a black box, hence hard to understand. A sp... [more] | NC2021-49 pp.17-22 |
| MBE, NC (Joint) |
2022-03-04 14:20 |
Online | Online | Investigation of machine learning methods for emotion discrimination by using phase synchronization of electroencephalogram Fumiya Hirooka, Jiro Okuda (Kyoto Sangyo Univ. Grad. Sch.) NC2021-74 |
This study investigated machine learning methods for emotion discrimination by using phase synchronization of electroenc... [more] | NC2021-74 pp.143-148 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [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] | |
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