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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 54  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SeMI, RCS, RCC, NS, SR
(Joint)
2023-07-13
16:10
Osaka Osaka University Nakanoshima Center + Online
(Primary: On-site, Secondary: Online)
[Short Paper] Detection of Hidden Nodes Using Wireless LAN Sensing Data
Hayato Mukasa, Fujii Takeo (UEC) SR2023-39
The Internet of Things (IoT) is attracting attention for monitoring the status of equipment in indoor environments such ... [more] SR2023-39
pp.52-54
IMQ, IE, MVE, CQ
(Joint) [detail]
2023-03-16
15:15
Okinawa Okinawaken Seinenkaikan (Naha-shi)
(Primary: On-site, Secondary: Online)
A Method for Fast Compression of Sign Bits of DCT Coefficients in Image Coding
Fuma Ito, Chihiro Tsutake, Keita Takahashi, Toshiaki Fujii (Nagoya Univ.) IMQ2022-56 IE2022-133 MVE2022-86
Compressing the signs of DCT coefficients is an intractable problem in image coding because of their equiprobable charac... [more] IMQ2022-56 IE2022-133 MVE2022-86
pp.178-181
R 2023-03-10
14:50
Hiroshima
(Primary: On-site, Secondary: Online)
Model selection between logistic and Gompertz models
Daisuke Satoh (NTT) R2022-52
A discrete Gompertz model and model selection between the Gompertz and logistic models are proposed. The proposed method... [more] R2022-52
pp.25-30
MI 2023-03-06
09:44
Okinawa OKINAWA SEINENKAIKAN
(Primary: On-site, Secondary: Online)
Machine learning models using CT images and clinical variable to classify tumors in testicular cancer
Shota Nakagawa, Masanobu Gido (University of Tsukuba), Satoshi Nitta (University of Tsukuba Hospital), Takahiro Kojima (Aichi Cancer Center Hospital), Hideki Kakeya (University of Tsukuba) MI2022-75
This paper presents machine learning methods to classify tumors in testicular cancer. The model combines CT images and c... [more] MI2022-75
pp.8-13
SP, IPSJ-SLP, EA, SIP [detail] 2023-03-01
17:10
Okinawa
(Primary: On-site, Secondary: Online)
Quantification of Voice Register Information including Mixed Voice based on Class Posterior Probabilities
Yu Kitamura, Anan Kikuchi, Daisuke Saito, Nobuaki Minematsu (UTokyo) EA2022-122 SIP2022-166 SP2022-86
Methods to distinguish between modal and falsetto have been proposed so far,
but there are few studies analyzing mixed ... [more]
EA2022-122 SIP2022-166 SP2022-86
pp.270-275
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
MBE, NC
(Joint)
2022-03-03
09:55
Online Online Observation for symptom of dementia based on features of Pupil light reflex and participant's age
Minoru Nakayama (Tokyo Tech.), Wioletta Nowak, Anna Zarowska (Wroclaw Univ. S&T) MBE2021-93
Pupil light reflex (PLR) were observed for elder subjects in order to examine an influence of stage of dimentia which wa... [more] MBE2021-93
pp.25-30
EMD, R 2021-02-12
14:35
Online Online Battery degradation diagnosis of mobile devices by using questionnaire data for individual usages
Minoru Asano, Shinji Yokogawa, You Ishigaki (UEC), Junichi Tominaga, Hamakazu Awazu (Keitaiichiba) R2020-36 EMD2020-27
Lithium-ion secondary battery, which increased high performance and capacity, widely used to ensure mobility for various... [more] R2020-36 EMD2020-27
pp.13-18
BioX 2020-11-25
13:50
Online Online A study on chewing evaluation using surface electromyogram
Yuta Shibahara (Miyazaki Univ), Takeshi Kikutani, Taishi Miyashita (Nippon Dent Univ), Hiroki Tamura (Miyazaki Univ) BioX2020-39
Japan is facing an aging society, and the proportion of elderly people suffering from dementia is increasing. As
dement... [more]
BioX2020-39
pp.20-25
HIP, HCS, HI-SIGCOASTER [detail] 2020-05-14
16:10
Online Online Estimation of recognizing emotions of facial images using EEG features
Satoru Waseda, Minoru Nakayama (TokyoTech) HCS2020-10 HIP2020-10
Relationship between viewer's scalp potentials and subjective impression
during viewing facial emotions was analysed u... [more]
HCS2020-10 HIP2020-10
pp.47-52
IMQ 2019-12-20
16:45
Tokyo   Effect of Visual and Auditory Adaptation on Material Perception
Takumi Nakamura, Kuangzhe Xu, Toshihiko Matsuka, Keita Hirai (Chiba Univ) IMQ2019-11
In this paper, we investigated the effects of visual and auditory adaptation on material perception. The target material... [more] IMQ2019-11
pp.9-13
R 2019-07-26
15:55
Iwate Ichinoseki Cultural Center More precise fitting of logistic curve model with missing data
Daisuke Satoh, Ryutaro Matsumura (NTT) R2019-18
A parameter estimating method based on a logistic curve model with missing data is proposed. Since the model is describe... [more] R2019-18
pp.25-29
R 2019-06-14
15:30
Tokyo Kikai-Shinko-Kaikan Bldg. Identification comparison of software fault-prone modules using nonlinear logistic regression models
Kazunari Yamanaka, Tadashi Dohi, Hiroyuki Okamura (Hiroshima U.) R2019-12
In this article, we compare several non-linear logistic regression models used in a fault-prone
identification problem... [more]
R2019-12
pp.19-24
NC, MBE
(Joint)
2019-03-05
16:40
Tokyo University of Electro Communications Influence of Alzheimer's Disease on Features of Waveforms in Pupil Light Reflex
Wioletta Nowak (Wroclaw Univ. of S&T), Minoru Nakayama (Tokyo Tech), Tomasz Krecicki (Wroclaw Medical Univ.), Andrzej Hachol (Wroclaw Univ. of S&T) MBE2018-103
Alzheimer's Disease (AD) patients were extracted using features of Pupil
Light Reflex (PLR) for 1 second chromatic sti... [more]
MBE2018-103
pp.89-92
NC, MBE
(Joint)
2018-12-15
15:30
Aichi Nagoya Institute of Technology Proposal of Analysis Accuracy Improvement Method by Logistic Regression in Single Nucleotide Polymorphism Analysis Using Next-Generation Sequencer
Ginji Azuma (Kindai Univ.), Atsushi Takahashi (NCVC), Naoki Ohboshi (Kindai Univ.) NC2018-37
Single nucleotide polymorphisms are known to be related to phenotypes, and analysis is actively performed. However, the ... [more] NC2018-37
pp.51-55
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Inference for Logitistic Regression Mixture Model with Local Variational Approximation and Study for Variational Free Energy
Fumito Nakamura, Ryosuke Konishi (Generic Solution), Yasushi Kiyoki (Keio) IBISML2018-48
A logistic regression mixture model (LRMM) is a mixed model of the Logistic regression model, and it is widely used in t... [more] IBISML2018-48
pp.29-36
KBSE, SS, IPSJ-SE [detail] 2018-07-18
10:30
Hokkaido   An analysis of the impact of temporal changes of developers' activities on the committer candidate prediction model
Daiki Yamasaki, Masao Ohira, Akinori Ihara, Yutaro Kashiwa, Tomoki Miyazaki (Wakayama Univ.) SS2018-4 KBSE2018-14
Many of large-scale open source projects have a serious problem in recruiting committers who have a privilege to commit ... [more] SS2018-4 KBSE2018-14
pp.19-24
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
14:45
Okinawa   Optimization of Gaussian Kernel Parameters for Kernel Logistic Regression
Kosuke Fukumori, Tomoya Wada, Toshihisa Tanaka (TUAT) EA2017-135 SIP2017-144 SP2017-118
The kernel logistic regression is a nonlinear classification model that effectively uses kernel methods, which are one o... [more] EA2017-135 SIP2017-144 SP2017-118
pp.185-190
MBE, NC
(Joint)
2018-03-14
14:25
Tokyo Kikai-Shinko-Kaikan Bldg. Effect of Alzheimer's Disease on factors in waveform features of Pupil Light Reflex
Wioletta Nowak (Wroclaw Univ. of S&T), Minoru Nakayama (Tokyo Tech), Krecicki Tomasz (Wroclaw Medical Univ.), Andrzej Hachol (Wroclaw Univ. of S&T) MBE2017-107
Pupil light reflex (PLR) for 1 second chromatic stimuli was analysed to
develop a procedure of detecting Alzheimer's D... [more]
MBE2017-107
pp.131-136
R 2017-10-20
14:25
Kumamoto   Logistic Curve's Parameter Fitting under Missing Data
Ryutaro Matsumura, Daisuke Satoh (NTT) R2017-45
The logistic difference equation can be solved by regression analysis to estimate parameters of logistic curve model wit... [more] R2017-45
pp.7-11
 Results 1 - 20 of 54  /  [Next]  
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