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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| OME | 2023-12-27 10:20 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Solution based LEDs with QD based emission layer and the improvement of device performance by multilayer deposition Eiji Itoh, Taisuke Sekino (Shinshu Univ.)  OME2023-74 |
In this research, we aimed to develop a multilayered light-emitting-diodes (QLEDs) with the semiconductor quantum dots a... [more] | OME2023-74 pp.33-37 |
| NLP | 2023-05-13 13:00 |
Fukushima | Kenshin Koriyama Cultural Center (Koriyama, Fukushima) | A study of optimal solution search behavior using GPSA with devided particle swarms Yoshikazu Yamanaka, Katsutoshi Yoshida (Utsunomiya Univ.) NLP2023-5 |
To find multiple optimal solutions simultaneously, the authors have proposed the gravitational particle swarm algorithm (... [more] | NLP2023-5 pp.20-22 |
| PRMU | 2022-09-14 10:15 |
Kanagawa | (Primary: On-site, Secondary: Online) |
Evaluation of Loss Functions for Low-Resolution Iris Recognition Using Deep Learning Rikuto Otsuka, Tsubasa Bora (UEC), Yuho Shoji, Yuka Ogino, Takahiro Toizumi (NEC), Ichino Masatsugu (UEC) PRMU2022-11 |
In this paper, we report the evaluation results of loss functions for low-resolution iris recognition using deep learnin... [more] | PRMU2022-11 pp.7-12 |
| PRMU, IPSJ-CVIM | 2022-05-13 11:00 |
Aichi | Toyota Technological Institute | Relationship between Perceptual and Image Qualities of Training and Reconstruction Images in Video Super-Resolution Hiroshi Mori, Norimichi Ukita (TTI) PRMU2022-5 |
Super resolution is a technique for converting low-resolution images into high-resolution images. Recent research has sh... [more] | PRMU2022-5 pp.24-29 |
| MI | 2022-01-26 13:00 |
Online | Online | Relationship between Image Quality and Learning Effect in Color Laparoscopic Images Generation by Generative Adversarial Networks Norifumi Kawabata (Hokkaido Univ.), Toshiya Nakaguchi (Chiba Univ.) MI2021-59 |
Improving of personal computer performance, it is possible for healthcare workers and related researchers to support for... [more] | MI2021-59 pp.59-64 |
| PRMU | 2021-12-16 11:00 |
Online | Online | Low-Resolution Iris Recognition with Image Super-Resolution for arbitrary magnification Tsubasa Bora (UEC), Takahiro Toizumi, Yuho Shoji, Yuka Ogino, Masato Tsukada (NEC), Masatsugu Ichino (UEC) PRMU2021-26 |
A low-resolution iris image reduces iris recognition accuracy. Some conventional researches tackle low-resolution iris r... [more] | PRMU2021-26 pp.13-18 |
| IE, CS, IPSJ-AVM, ITE-BCT [detail] | 2020-11-27 15:00 |
Online | Online | Comparative Study of Channel Estimation using Deep-learning based Super-resolution Daiki Maruyama, Kenji Kanai, Jiro Katto (Waseda Univ.) CS2020-73 IE2020-32 |
Recently, application of deep learning into communication systems are getting lots of attention to researchers. Especial... [more] | CS2020-73 IE2020-32 pp.39-44 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2019-03-14 14:20 |
Kagoshima | Kagoshima University | Implementation and Evaluation of Total Variation Regularization Decomposition for Super Resolution using an Inexpensive Single Board Computer Hiromasa Takeda, Taiki Kondo, Hiroto Kizuna, Hiroyuki Sato, Eiji Sugino (Iwate Pref. Univ.) IMQ2018-39 IE2018-123 MVE2018-70 |
With the advent of large and high resolution displays in recent years, large screen electronic signage such as digital s... [more] | IMQ2018-39 IE2018-123 MVE2018-70 pp.97-102 |
| NS, IN (Joint) |
2018-03-02 09:00 |
Miyazaki | Phoenix Seagaia Resort | Evolutionary Network Power-Saving Method based on Pareto Optimal Control Yosuke Akishita, Yuichi Ohsita, Masayuki Murata (Osaka Univ.) IN2017-113 |
The power consumption of networks has been increasing as the service over the Internet becomes popular, and has become a... [more] | IN2017-113 pp.141-146 |
| NLP | 2016-09-14 15:20 |
Hyogo | Konan Univ. | A study of the solution search performance in the PSO whose particle generates multiple solution candidates Keita Oida, Kenya Jin'no (NIT) NLP2016-52 |
One of meta-heuristics is a particle swarm optimization (PSO). Since the parameter of the velocity of the particles con... [more] |
NLP2016-52 pp.41-44 |
| CAS, SIP, MSS, VLD, SIS [detail] | 2014-07-09 15:50 |
Hokkaido | Hokkaido University | high speed super-resolution based on compressed sensing Tomohiro Yamashita, Jaehoon Yu, Yoshinori Takeuchi, Masaharu Imai (Osaka Univ.) CAS2014-16 VLD2014-25 SIP2014-37 MSS2014-16 SIS2014-16 |
This paper proposes a speed-up superresolution(SR) method based on compressed sensing, where SR is a class of technique... [more] |
CAS2014-16 VLD2014-25 SIP2014-37 MSS2014-16 SIS2014-16 pp.75-80 |
| MBE, NC (Joint) |
2012-03-16 10:15 |
Tokyo | Tamagawa University | Exploring ability of various Insensitive Differential Evolution Itsuki Handa, Toshimichi Saito (HU) NC2011-180 |
This paper presents an insensitive differential evolution for multi-solution problems. The algorithm consists of globa... [more] |
NC2011-180 pp.347-352 |
| RCS | 2010-06-18 14:55 |
Kyoto | Kyoto Univ. | Study on MIMO Wireless Transmission with Constant Envelope Modulation and a Low-Resolution ADC Osamu Muta, Hiroshi Furukawa (Kyushu Univ.) RCS2010-44 |
The purpose of our research is to increase relay channel capacity in wireless backhaul systems and develop a small siz... [more] |
RCS2010-44 pp.157-162 |
| PRMU, TL | 2006-02-23 10:30 |
Ibaraki | Analytical DP matching and its application to pattern recognition Seiichi Uchida, Hiroaki Sakoe (Kyushu Univ.) |
DP (dynamic programming) matching is one of the most fundamental techniques for various pattern recognition and image ... [more] |
TL2005-56 PRMU2005-191 pp.43-48 |
|
| ICD, CPM | 2005-09-08 10:55 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Visualization of High Frequency Electromagnetic Field over Fine Circuits by Magnetooptic/Electrooptic Probe Mizuki Iwanami, Shigeki Hoshino, Norio Masuda (NEC), Masato Kishi (Univ. of Tokyo), Masahiro Tsuchiya (NICT) |
To realize a electromagnetic field probe that is capable of contributing to an electrical design, especially a low-noise... [more] | CPM2005-88 ICD2005-98 pp.19-24 |
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