| 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 # | |
| ASN, NS, RCS, SR, RCC (Joint) |
2018-07-12 09:30 |
Hokkaido | Hakodate Arena | Construction of Time-Space Radio Environment Database using HMM for Cooperative Sensing Yuya Aoki, Takeo Fujii (UEC)  SR2018-30 |
In recent years, many researchers focus on a measurement-based Radio Environment Database (RED) that utilizes the actual... [more] | SR2018-30 pp.57-64 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 13:00 |
Okinawa | Okinawa Institute of Science and Technology | Variable Order Infinite Hidden Markov Models Kei Uchiumi (Denso ITLab), Daichi Mochihashi (ISM) IBISML2018-5 |
[more] | IBISML2018-5 pp.31-38 |
| RCS, SR, SRW (Joint) |
2018-02-28 15:40 |
Kanagawa | YRP | A community-based anomaly detection system by the synergetic use of mobile sensing and delay tolerant networks with cooperative data processing technique Yoshito Watanabe, Yozo Shoji (NICT) SR2017-115 |
This paper proposes a novel cooperative anomaly detection system that uses mobile sensing and delay tolerant network (DT... [more] | SR2017-115 pp.25-30 |
| PRMU, MVE, IPSJ-CVIM [detail] | 2018-01-18 09:30 |
Osaka | Trajectory semantic segmentation based on behavior models Daisuke Ogawa, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda (Hiroshima Univ.) PRMU2017-112 MVE2017-33 |
In many cases, such as trajectories clustering and classification, we often divide a trajectory into segments as preproc... [more] | PRMU2017-112 MVE2017-33 pp.1-7 |
|
| IBISML | 2017-11-09 13:00 |
Tokyo | Univ. of Tokyo | Hidden Semi-Markov Model Representing State Overlap for Multiple Sequential Data Input Hiromi Narimatsu, Hiroyuki Kasai (UEC) IBISML2017-49 |
This paper proposes an extended hidden semi-Markov model (HSMM) to handle multiple sequence inputs. The significant limi... [more] | IBISML2017-49 pp.109-114 |
| EA, ASJ-H | 2017-10-21 14:30 |
Toyama | Ushidake-Onsen | Writer identification with sounds in signing Daichi Asakura (Mie Univ), Nishino Takanori (Meijo Univ), Naruse Hiroshi (Mie Univ) EA2017-45 |
(To be available after the conference date) [more] | EA2017-45 pp.11-12 |
| HCS, HIP, HI-SIGCOASTER [detail] | 2017-05-17 15:40 |
Okinawa | Okinawa Industry Support Center | Estimation of hidden states for success and failure of consultation
-- Time series analysis of interaction between two people -- Hidehito Honda, Ryosuke Hisamatsu (Univ. of Tokyo), Yoshimasa Ohmoto (Kyoto Univ.), Takatomi Kubo, Kazushi Ikeda (NAIST), Kazuhiro Ueda (Univ. of Tokyo) HCS2017-45 HIP2017-45 |
We examined how two people interacted with each other during travel consultation based on their verbal and nonverbal beh... [more] | HCS2017-45 HIP2017-45 pp.293-296 |
| HCGSYMPO (2nd) |
2016-12-07 - 2016-12-09 |
Kochi | Kochi City Culture Plaza (CUL-PORT) | Sign Language Recognition Performance Improvements by Feature Elements of Hidden Markov Model Hirotoshi Shibata, Tatsunori Ozawa, Hiromitsu Nishimura, Hiroshi Tanaka (Kanagawa Institute of Technology), Daisuke Kobayashi, Michio Iwamoto, Syuji Kato (KCC corp.) |
The authors have been investigating method of sign language recognition using colored gloves and optical camera. We are ... [more] | |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | [Poster Presentation]
Ryo Nishikimi, Eita Nakamura, Katsutoshi Itoyama, Kazuyoshi Yoshii (Kyoto Univ.) IBISML2016-93 |
(To be available after the conference date) [more] | IBISML2016-93 pp.337-343 |
| ITE-ME, IE, EMM, LOIS, IEE-CMN [detail] | 2016-09-16 15:30 |
Aichi | Aichi Prefectural University | A Study on Colorization in Photo-Realistic Facial Animation Synthesis from Text Based on HMM and DNN with Animation Unit Kazuki Sato, Takashi Nose, Akinori Ito (Tohoku Univ.) LOIS2016-27 IE2016-64 EMM2016-53 |
We propose a technique for synthesizing photo-realistic facial animation from a text based on hidden Markov model (HMM) ... [more] | LOIS2016-27 IE2016-64 EMM2016-53 pp.67-72 |
| WIT | 2016-07-15 16:20 |
Yamanashi | University of Yamanashi Organization for Information Management | Fundamental Study on Automatic Recognition of Non-Manual Signals in JSL using HMM Rina Kato, Shinji Sako, Tadashi Kitamura (NITech) WIT2016-23 |
We work on automatic Japanese sign Language (JSL) recognition using hidden Markov models (HMMs). In general, sign langua... [more] | WIT2016-23 pp.15-19 |
| ICM | 2016-07-07 15:05 |
Hokkaido | Multiple Isolating Actions Extraction from Action Logs for Clarifying Trouble-shooting Process Akio Watanabe, Yoichi Matsuo, Keishiro Watanabe, Keisuke Ishibashi, Ryoichi Kawahara (NTT) ICM2016-13 |
Virtualization of ICT system has made more convenient of its use. However, complicated system architecture by virtualiz... [more] |
ICM2016-13 pp.27-32 |
|
| AI | 2016-06-27 16:40 |
Tokyo | A Study of Evaluation of Psychological State for Increasing the Efficiency of Office Work Susumu Shirayama, Masanobu Namiki, Shota Imafuku, Rie Osawa (Univ. of Tokyo) AI2016-11 |
It is considered that improvement of the physical environment in office is effective for increasing the efficiency of of... [more] | AI2016-11 pp.55-60 |
|
| PRMU, SP, WIT, ASJ-H | 2016-06-13 09:30 |
Tokyo | Image recognition based on discriminative models using features generated from separable lattice HMMs Yoshinari Tsuzuki, Kei Sawada, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Inst. of Tech.) PRMU2016-36 SP2016-2 WIT2016-2 |
One of the major problems in image recognition is degradation in the recognition performance caused by geometric variati... [more] | PRMU2016-36 SP2016-2 WIT2016-2 pp.7-12 |
|
| PRMU, BioX | 2016-03-25 13:00 |
Tokyo | Boredom state estimation from spontaneous behaviors in multiparty conversations including a robot agent Yasuhiro Shibasaki (Tokyo Tech), Kotaro Funakoshi (HRI-JP), Koichi Shinoda (Tokyo Tech) BioX2015-61 PRMU2015-184 |
Conversation systems need to have the abilities to grasp the human internal information such as bore- dom state to becom... [more] | BioX2015-61 PRMU2015-184 pp.119-124 |
|
| ICSS, IPSJ-SPT | 2016-03-04 10:30 |
Kyoto | Academic Center for Computing and Media Studies, Kyoto University | Static Detection of ROP Chain Based on Hidden Markov Model Toshinori Usui, Tomonori Ikuse, Makoto Iwamura, Takeshi Yada (NTT) ICSS2015-59 |
Threats of targeted attacks have been widely observed. The targeted attacks generally utilize malicious documents that c... [more] | ICSS2015-59 pp.71-76 |
| PRMU, CNR | 2016-02-21 14:00 |
Fukuoka | Parameter sharing structures of separable lattice HMMs using mixture output distributions for image recognition Masato Sukegawa, Kei Sawada, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Inst. of Tech.) PRMU2015-138 CNR2015-39 |
In image recognition systems, it is important to deal with geometrical variations such as size and location. Separable l... [more] | PRMU2015-138 CNR2015-39 pp.37-42 |
|
| IBISML | 2015-11-27 14:00 |
Ibaraki | Epochal Tsukuba | [Poster Presentation]
Evaluation of Hidden Semi-Markov Models with Interval State Node Hiromi Narimatsu, Hiroyuki Kasai (UEC) IBISML2015-84 |
This paper presents an extended HMM that models both sequence length and sequence interval of sequential data. The struc... [more] | IBISML2015-84 pp.233-240 |
| WIT | 2015-08-26 11:30 |
Nagano | Shinshu University Faculty of Engineering | A study on phonemic weight estimation for HMM-based sign language recognition using phonemic structure Shinji Sako, Kaho Sugi, Tadashi Kitamura (NIT) WIT2015-47 |
We work on automatic Japanese sign Language (JSL) recognition using hidden Markov models (HMMs). An important issue for ... [more] | WIT2015-47 pp.59-64 |
| NC, MBE | 2015-03-17 10:25 |
Tokyo | Tamagawa University | Reconstruction of three-dimensional multi-finger movements from magnetoencephalography with a state transition model Yoshiki Azuma, Yumi Shikauchi (Kyoto Univ.), Yutaka Nakamura (Osaka Univ.), Jun-ichiro Hirayama (ATR), Shin Ishii (Kyoto Univ.) MBE2014-152 NC2014-103 |
We proposed a new reconstruction model to reconstruct multi-finger movements from MEG signals. We extracted features o... [more] |
MBE2014-152 NC2014-103 pp.199-204 |
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