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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 130  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
EA, US, SP, SIP, IPSJ-SLP [detail] 2021-03-03
16:45
Online Online An optimal prediction of phoneme under Bayes criterion by weighting multiple hidden Markov models
Taishi Yamaoka, Shota Saito, Toshiyasu Matsushima (Waseda Univ.) EA2020-76 SIP2020-107 SP2020-41
In this paper, we propose a prediction method for prediction problems using a hidden Markov model. Specifically, it is a... [more] EA2020-76 SIP2020-107 SP2020-41
pp.97-102
CAS, ICTSSL 2021-01-29
10:10
Online Online Consideration of Switching by Chaotic Neurodynamics for Asymmetric TSPs by using Hidden Markov Model
Tomoya Matsuno, Toshihiro Tachibana (Shonan Inst. of Tech.), Masaharu Adachi (Tokyo Denki Univ.) CAS2020-59 ICTSSL2020-44
Several methods for solving the asymmetric traveling salesman problem using chaotic neural networks is proposed by Tachi... [more] CAS2020-59 ICTSSL2020-44
pp.107-110
IT 2020-12-02
09:40
Online Online Approximation Method for Bayes Optimal Prediction in Phoneme Recognition Problem
Taishi Yamaoka, Shota Saito, Toshiyasu Matsushima (Waseda Univ.) IT2020-30
In this paper, we propose a method of phoneme recognition. In the previous studies on phoneme recognition using the Hidd... [more] IT2020-30
pp.32-37
HIP 2020-10-08
13:10
Online Online Investigation on Modeling Dynamic Properties of Eye Movement in Impression Evaluation of Painting by Hidden Markov Models
Shun Oue (Hosei Univ.), Yuiko Sakuta (Jissen Women's Univ.), Shigeru Akamatsu (Hosei Univ.) HIP2020-32
In this study, we analyzed whether there is any relationship between impression evaluation for painting and eye movement... [more] HIP2020-32
pp.1-6
MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] 2020-05-29
14:10
Online Online Construction of Hidden Markov Models for Brain Tumor Segmentation
Takuya Honda, Yuta Nakahara, Matushima Toshiyasu (Waseda Univ.) SIP2020-13 BioX2020-13 IE2020-13 MI2020-13
Brain tumor segmentation is one of the systems that a computer, which has attracted attention in recent years, assists d... [more] SIP2020-13 BioX2020-13 IE2020-13 MI2020-13
pp.61-66
PRMU 2019-12-19
10:30
Oita   A switching Markov model for evaluation of food functionality
Tsukasa Hokimoto, Toshio Uchiyama (HIU) PRMU2019-46
For analytic purposes of the scientific processes on how food influence our health, the measurement data on medical or g... [more] PRMU2019-46
pp.1-6
HCGSYMPO
(2nd)
2019-12-11
- 2019-12-13
Hiroshima Hiroshima-ken Joho Plaza (Hiroshima) Investigating relationship between impression evaluation of painting and eye movement pattern through hidden Markov model
Shun Oue (Hosei Univ.), Yuiko Sakuta (Jissen Women's Univ.), Shigeru Akamatsu (Hosei Univ.)
In this study, we analyzed whether there is any relationship between impression evaluation for painting and eye movement... [more]
SR
(2nd)
2019-11-04
- 2019-11-05
Overseas Rutgers University Inn & Conference Center, NJ, USA Traffic Prediction in Future Mobile Networks using Hidden Markov Model
Sumeet Dash (Shiv Nadir Univ.), Sumit Maheshwari (Rutgers Univ.), Sudipta Mahapatra (IIT Kharagpur)
The recent advances in the wireless network architectures are mainly focused on improving the end-user performance as me... [more]
IMQ, IE, MVE, CQ
(Joint) [detail]
2019-03-14
09:30
Kagoshima Kagoshima University Investigation on characteristics of face perception in terms of dynamic properties of eye movement
Shun Ohue, Ryoko Yamada, Shigeru Akamatsu (Hosei Univ.) IMQ2018-26 IE2018-110 MVE2018-57
We investigated the relationship between face recognition performance and eye movement between individuals, face images,... [more] IMQ2018-26 IE2018-110 MVE2018-57
pp.19-24
SR 2019-01-24
15:20
Fukushima Corasse, Fukushima city (Fukushima prefecture) An Error Correction Technique with the Viterbi Algorithm for a Machine-Learning-Based Classifier
Yoshito Watanabe, Yozo Shoji (NICT) SR2018-105
This paper proposes a novel technique to correct errors that can be caused in the decisions made by a machine learning (... [more] SR2018-105
pp.57-61
NLP, NC
(Joint)
2019-01-24
15:40
Hokkaido The Centennial Hall, Hokkaido Univ. Detection of mouse sleep-stages using hidden Markov model and random forest
Shun Matsuzaki (The University of Tokyo), Masanori Sakaguchi (University of Tsukuba), Takaaki Ohnishi (The University of Tokyo) NLP2018-123
Fully automatic determination of the sleep stages (non-REM, REM, arousal) of the mouse is important in improving the mem... [more] NLP2018-123
pp.143-148
HCGSYMPO
(2nd)

Mie Sinfonia Technology Hibiki Hall Ise Understanding face recognition performance in terms of individual variation of eye movement learned by HMM
Shun Ohue, Ryoko Yamada, Shigeru Akamatsu (Hosei Univ.)
We investigated the relationship between face recognition performance and eye movement between individuals.
In this wor... [more]

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
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 Regression Method for Noisy Inputs based on Naradaya-Watson Estimator constructed from Noiseless Training Data
Ryo Hanafusa, Takeshi Okadome (Kwansei Gakuin Univ.) IBISML2017-46
The regression method proposed in this paper produces a regression function for noisy inputs that minimizes the expected... [more] IBISML2017-46
pp.85-92
HCS, HIP, HI-SIGCE [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
SP 2017-01-21
16:35
Tokyo The University of Tokyo Simultaneous modeling of acoustic feature sequences and its temporal structures for DNN-based speech synthesis
Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda (Nagoya Inst. of Tech.) SP2016-76
In statistical parametric speech synthesis, a hidden Markov model (HMM) is widely used as an acoustic model. Recently, d... [more] SP2016-76
pp.71-76
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]
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
 Results 1 - 20 of 130  /  [Next]  
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