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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| 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 |
| SS, MSS | 2020-01-15 11:20 |
Hiroshima | Modeling of Prediction Processes based on Learning Colored Petri Nets Ibuki Kawamitsu, Morikazu Nakamura (Univ. of the Ryukyus) MSS2019-53 SS2019-37 |
This paper presents a modeling approach to visualize the prediction process of machine learning based on learning colore... [more] | MSS2019-53 SS2019-37 pp.73-78 |
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| DE, IPSJ-DBS | 2019-12-24 09:35 |
Tokyo | National Institute of Informatics | A Book Prediction Model Based on User's Book Arrangement and It's Evaluation Tatsuya Miyamoto, Daisuke Kitayama (Kogakuin Univ.) DE2019-21 |
In recent years, the evaluation of recommender systems has focused on not only accuracy but other aspects. This is bec... [more] |
DE2019-21 pp.1-5 |
| IT | 2019-07-25 14:25 |
Tokyo | NATULUCK-Iidabashi-Higashiguchi Ekimaeten | Bayes Optimal Prediction and Its Approximative Algorithm on Model Including Cluster Explanatory Variables and Regression Explanatory Variables Haruka Murayama, Shota Saito, Yuta Nakahara, Toshiyasu Matsushima (Waseda Univ.) IT2019-16 |
In this research, data are assumed to be divided in clusters based on a part of the continuous explanatory variables, an... [more] | IT2019-16 pp.5-10 |
| MBE | 2019-07-20 11:20 |
Tokushima | Near future drowsiness prediction using support vector regression analysis of electroencephalogram parameters Izzat Akbar, Arthur Rumagit, Mitaku Utsunomiya, Takamasa Morie, Tomohiko Igasaki (Kumamoto Univ.) MBE2019-21 |
Traffic accident becomes a global concern recently. One of the causes is drowsy driving. Previous studies tried to solve... [more] | MBE2019-21 pp.13-18 |
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| 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 |
| IA, ICSS | 2019-06-06 14:40 |
Miyagi | Research Institute for Electrical Communication, Tohoku University | RSSI Prediction of LoRa in Indoor Environment with Support Vector Regression Mai Hirata, Hideya Ochiai, Hiroshi Esaki (UTokyo) IA2019-1 ICSS2019-1 |
In this study, we focused on LoRa which is one of the LPWA.We proposed the method to estimate the RSSI from the environm... [more] | IA2019-1 ICSS2019-1 pp.1-6 |
| ITS, IEE-ITS | 2019-03-04 10:55 |
Kyoto | Kyoto Univ. | Improvement in travel time prediction based on linear regression models Shigeharu Toyoda, Ken-ichi Masuda, Kentarou Takaki (SEI) ITS2018-87 |
In the case of the database of the Japan Digital Road Map Association, there are 1.54 million road links even in Japan's... [more] | ITS2018-87 pp.5-10 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | IBISML2018-87 |
A learning algorithm to perform sparse estimation method can estimate effective parameters of a polynomial regression mo... [more] | IBISML2018-87 pp.321-328 |
| 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 |
|
| IN | 2018-01-23 14:50 |
Aichi | WINC AICHI | BPM Estimation of Anime Incidental Music by Multiple Regression Analysis of Spoken Lines Yuta Ito, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2017-88 |
Incidental music is background music of TV drama, anime, films, Plays, and so forth, and it is an important element to d... [more] | IN2017-88 pp.97-102 |
| SP, SIP, EA | 2017-03-01 12:40 |
Okinawa | Okinawa Industry Support Center | [Poster Presentation]
Dual-Sparsification of Kernel Regression Based on Sampling Atsushi Kojima, Toshihisa Tanaka (TUAT) EA2016-102 SIP2016-157 SP2016-97 |
When the input pattern have redundant features in regression analysis or pattern recognition, the prediction accuracy is... [more] | EA2016-102 SIP2016-157 SP2016-97 pp.115-118 |
| IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2017-02-20 10:30 |
Hokkaido | Hokkaido Univ. | Predicting View and Exit Rates on MOOC Yusuke Fukushima, Toshihiko Yamasaki, Kiyoharu Aizawa (UTokyo), Kenshiro Mori, Kensho Suzuki (Schoo) |
While massive open online courses (MOOC) have gained increasing popularity in recent years, predicting the number of stu... [more] | |
| IE, ITE-ME, ITE-AIT [detail] | 2016-10-06 11:30 |
Fukuoka | A Method for Predicting Image Region Specified by Query Texts Kou Endo (TUT), Kotarou Funakoshi, Eric Nichols (HRI-J), Masaki Aono (TUT) IE2016-66 |
We propose a method to identify the area in the image that corresponds to a user's text query. The input to the system i... [more] | IE2016-66 pp.7-12 |
|
| EA, ASJ-H | 2016-08-09 13:30 |
Miyagi | Tohoku Gakuin Univ., Tagajo Campus | Improvement to an Objective Binaural Intelligibility Prediction Method Kazuya Taira, Kazuhiro Kondo (Yamagata Univ.) EA2016-21 |
We attempted to improve the binaural intelligibility estimation method proposed in our previous paper. The number of dat... [more] | EA2016-21 pp.7-12 |
| MICT, ASN, MoNA (Joint) |
2016-01-29 10:15 |
Kanagawa | Hotel Okada | Analysis of Family Electricity Data Obtained by Smart Meters Kazuki Omomo, Yuta Kobiyama, Qiangfu Zhao (Univ. Aizu) ASN2015-90 |
In this paper, by using electricity data obtained by smart meters located in residential houses, we try to predict futur... [more] | ASN2015-90 pp.63-68 |
| SP | 2016-01-14 13:00 |
Kanagawa | Sunpian Kawasaki | [Invited Talk]
Articulatory controllable statistical parametric speech synthesis using EMA data Junichi Yamagishi (NII/Univ. Edinburgh) SP2015-88 |
This paper describes speech processing work in which articulator movements are used in conjunction with the acoustic spe... [more] | SP2015-88 pp.19-24 |
| SIP | 2015-08-20 10:20 |
Tokyo | National Institute of informatics | A Study of High-precision Activity Meter by Microwave Sensor Using Machine Learning Michiyo Hiramoto, Kurato Maeno (OKI) SIP2015-58 |
We have studied a high-precision activity meter without any wearable devices for the elderly who intend to stay at their... [more] | SIP2015-58 pp.41-46 |
| R | 2015-07-31 15:10 |
Aomori | On Software Quality Prediction Based on Generalized Linear Models Shinji Inoue, Shigeru Yamada (Tottori Univ.) R2015-18 |
Statistical analysis approaches are often discussed for statistical software quality prediction based on software proces... [more] | R2015-18 pp.25-30 |
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| NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-25 10:20 |
Okinawa | Okinawa Institute of Science and Technology | e-Bagging: The Information Geometric Dual of Breiman's Bagging
-- An Application to the Nadaraya-Watson Regression with the k-Nearest Neighbor Crossover Kernel -- Naoki Hamada, Hiroyuki Higuchi, Katsumi Homma (Fujitsu Labs.) IBISML2015-23 |
The $k$-nearest neighbor crossover kernel, which we proposed recently, is a very flexible kernel that is virtually equiv... [more] | IBISML2015-23 pp.187-194 |
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