| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| US | 2022-02-24 15:35 |
Online | Online | Non-destructive inspection of shotcrete specimens by noncontact acoustic inspection method Tsuneyoshi Sugimoto, Kazuko Sugimoto (Toin Univ.), Noriyuki Utagawa, Chitose Kuroda (SatoKogyo)  US2021-73 |
Shotcrete is widely used for supporting underground cavities because of its excellent workability. However, in a high pl... [more] | US2021-73 pp.21-26 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-21 14:25 |
Online | Online | A Note on Visual Sentiment Prediction Based on Few-shot Learning using Knowledge Distillation Yingrui Ye, Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
The prediction of visual sentiment can be useful to understand users' behaviors. Emotion theories underlying the sentime... [more] | |
| EA, US, SP, SIP, IPSJ-SLP [detail] | 2021-03-04 09:50 |
Online | Online | Subjective Evaluation of Recording System for Personal 3D Sound Field Reproduction Fumi Hanyu, Toshiyuki Kimura (Tohoku Gakuin Univ.) EA2020-81 SIP2020-112 SP2020-46 |
We have proposed the personal 3D sound field reproduction in which the sound recorded by eight directional microphones i... [more] | EA2020-81 SIP2020-112 SP2020-46 pp.128-133 |
| PRMU | 2020-12-17 14:40 |
Online | Online | Belonging Network
-- Few-shot One-class Image Classification for Classes with Various Distributions -- Takumi Ohkuma, Hideki Nakayama (UT) PRMU2020-44 |
Few-shot one-class image classification is the task of recognizing a particular class while rejecting test images that d... [more] | PRMU2020-44 pp.36-41 |
| PRMU | 2020-12-17 16:20 |
Online | Online | [Short Paper]
Few-Shot Incremental Learning by Unifying with Variational Autoencoder Keita Takayama, Kuniaki Uto, Koichi Shinoda (TokyoTech) PRMU2020-48 |
We propose a few-shot incremental learning method using a variational autoencoder for deep learning. In incremental lear... [more] | PRMU2020-48 pp.58-62 |
| PRMU | 2020-12-18 14:25 |
Online | Online | Zero-shot generative model considering attribute uncertainty Yuta Sakai (Waseda Univ.), Kenta Mikawa (SIT), Masayuki Goto (Waseda Univ.) PRMU2020-59 |
Classification problems in machine learning remain an important research topic. In general, classification estimates unk... [more] | PRMU2020-59 pp.122-127 |
| PRMU | 2020-12-18 14:55 |
Online | Online | Regularization Using Knowledge Distillation in Learning Small Datasets Ryota Higashi, Toshikazu Wada (Wakayama Univ.) PRMU2020-61 |
Knowledge distillation is a method mainly used for compressing deep learning models, but it has recently gained attentio... [more] | PRMU2020-61 pp.133-138 |
| HCGSYMPO (2nd) |
2020-12-15 - 2020-12-17 |
Online | Online | Key Icon Concealed Graphical Authentication System Using Image Distortion Takayuki Kawamura (Tsukuba Univ.), Toshio Suzuki (TUS), Keiichi Zempo (Tsukuba Univ.) |
Graphical authentication systems has an advantage over existing letters password systems in that it is easier to remembe... [more] | |
| ICM | 2020-07-17 09:25 |
Online | Online | Study on which data we should label in a few-shot learning for service identification over encrypted web services Shouta Yoshida, Yutaka Eguchi, Kohei Shiomoto (TCU) ICM2020-14 |
It is very important to monitor and control the communication traffic to cope with the increasing communication traffic... [more] |
ICM2020-14 pp.37-42 |
| PRMU, IPSJ-CVIM | 2020-03-16 11:00 |
Kyoto | (Cancelled but technical report was issued) |
[Short Paper]
Few-shot Character Image Generation with Deep Metric Learning Haruka Aoki, Koki Tsubota, Hikaru Ikuta, Kiyoharu Aizawa (Tokyo Univ.) PRMU2019-66 |
(To be available after the conference date) [more] | PRMU2019-66 pp.11-12 |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2020-03-06 09:45 |
Fukuoka | Kyushu Institute of Technology (Cancelled but technical report was issued) |
Pose-based Shot Detection in a Badminton Doubles Competition Video Satoru Yamagishi, Yoshiteru Yamamoto, Keisuke Doman, Yoshito Mekada (Chukyo Univ.) IMQ2019-54 IE2019-136 MVE2019-75 |
The movement in formation of players is a key factor to score a point in badminton doubles competition. It is, however,... [more] |
IMQ2019-54 IE2019-136 MVE2019-75 pp.199-203 |
| US | 2020-02-28 13:10 |
Tokyo | Defect detection for shotcrete in ceiling of underground cavity by noncontact acoustic inspection method
-- Alternative method of hammering inspection by acoustic irradiation induced vibration from a long distance -- Tsuneyoshi Sugimoto, Kazuko Sugimoto (Toin Univ.), Noriyuki Utagawa, Chitose Kuroda (SatoKogyo), Hiroshi Morioka, Shigeru Tsuruta (TEPCO), Takayuki Nakagawa, Ataru Honda (TEPSCO), Naoto Sugisaki, Takao Yamazaki (tousetu) US2019-100 |
Shotcrete is widely used for supporting underground cavities because of its excellent workability. However, in a high pl... [more] | US2019-100 pp.7-12 |
|
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-27 13:45 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
Zero-Shot Conditional Inpainting Naoki Kato, Toshihiko Yamasaki (UTokyo) ITS2019-36 IE2019-74 |
Image processing for objects of the unseen classes is sometimes needed, and one of the solutions of that is ``zero-shot ... [more] | ITS2019-36 IE2019-74 pp.189-194 |
| EMM | 2020-01-27 14:30 |
Miyagi | Tohoku Univ. | iPhone application development to embed URL at taking screenshots Kenta Nango, Masaki Kawamura (Yamaguchi Univ.) EMM2019-97 |
We are developing an iPhone application which can embed a URL into a screenshot image of a web page by using digital wat... [more] | EMM2019-97 pp.17-21 |
| PRMU | 2019-12-20 10:45 |
Oita | An Efficient Block-wise Object Detection Method using Consecutive Frames for High Resolution Video Kazuki Hozumi, Yoichi Tomioka (UoA) PRMU2019-57 |
In recent years, in the fields such as surveillance cameras and in-vehicle camera systems, efficient deep-learning-based... [more] | PRMU2019-57 pp.69-74 |
|
| HCGSYMPO (2nd) |
2019-12-11 - 2019-12-13 |
Hiroshima | Hiroshima-ken Joho Plaza (Hiroshima) | Estimation of Braille Block Type and Position from Wearable Camera Shotaro Nakamura, Hidehiko Shishido, Itaru Kitahara, Yoshinari Kameda (U-Tsukuba) |
(To be available after the conference date) [more] | |
| SeMI, RCS, NS, SR, RCC (Joint) |
2019-07-11 15:25 |
Osaka | I-Site Nanba（Osaka） | Few-shot Learning based on Prototypical Network to Understand Area Service Level in LTE Networks Shogo Aoki (Waseda Univ.), Kohei Shiomoto (TCU), Chin Lam Eng, Sebastian Backstad (Ericsson Japan) RCC2019-42 NS2019-78 RCS2019-135 SR2019-54 SeMI2019-51 |
In case a base station in mobile network malfunction, it is crucial to classify a service degradation event and identify... [more] | RCC2019-42 NS2019-78 RCS2019-135 SR2019-54 SeMI2019-51 pp.151-156(RCC), pp.177-182(NS), pp.173-178(RCS), pp.183-188(SR), pp.165-170(SeMI) |
| PRMU, BioX | 2019-03-18 15:00 |
Tokyo | Reali-time Object Detection based on SSD Yuya Yamashige, Masaki Aono (TUT) BioX2018-60 PRMU2018-164 |
In recent years, attention has been paid to developing object detection methods from images, based on deep learning. In ... [more] | BioX2018-60 PRMU2018-164 pp.181-186 |
|
| PRMU, BioX | 2018-03-18 16:45 |
Tokyo | Evaluation of the Shot Boundary Detection Method based on Unsupervised Learning from Video Big Data Norio Katayama, Hiroshi Mo, Shin'ichi Satoh (NII) BioX2017-53 PRMU2017-189 |
Video data is a sequence of video frames and their temporal continuity is an essential property of video stream. In th... [more] |
BioX2017-53 PRMU2017-189 pp.103-108 |
|
| CPSY, DC, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC [detail] | 2018-03-07 16:35 |
Shimane | Okinoshima Bunka-Kaikan Bldg. | A System for Analyzing Memory Snapshot with NVDIMM Masahito Misu, Shinobu Miwa, Hayato Yamaki, Hiroki Honda (UEC) CPSY2017-137 DC2017-93 |
Non-Volatile DIMM (NVDIMM), which has the speed comparable to DRAM DIMM, is lately available and being introduced into v... [more] | CPSY2017-137 DC2017-93 pp.107-112 |
[Return to Top Page]