Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-02-29 09:30 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Simultaneous Estimation of Transfer Coefficients and Signals of Sound-to-Light Conversion Device Blinky Under Saturation Using Non-negative Matrix Factorization Kosuke Nishida, Natsuki Ueno, Nobutaka Ono (TMU), Daichi Kitamura (Kagawa NCT) EA2023-65 SIP2023-112 SP2023-47 |
In this study, we propose a method to estimate the intensity of optical signals emitted by sound-to-optical conversion d... [more] |
EA2023-65 SIP2023-112 SP2023-47 pp.25-30 |
IMQ |
2023-12-22 14:00 |
Toyama |
University of Toyama |
[Invited Lecture]
Machine learning application for 2D/3D data analysis in material science Kentaro Kutsukake (RIKEN) IMQ2023-9 |
In materials science, data is becoming increasingly complex, high-dimension, large-scale, and numerous, consequently, hi... [more] |
IMQ2023-9 pp.1-3 |
DE, IPSJ-DBS, IPSJ-IFAT [detail] |
2023-09-22 09:25 |
Fukuoka |
Kitakyushu International Conference Center |
DE2023-19 |
(To be available after the conference date) [more] |
DE2023-19 pp.48-53 |
NLP, MSS |
2023-03-17 14:50 |
Nagasaki |
(Primary: On-site, Secondary: Online) |
Reformulation of Optimization Problem in Randomized NMF and Proposal of A Novel Iterative Update Algorithm Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) MSS2022-105 NLP2022-150 |
As an approach to efficiently perform large-scale Nonnegative Matrix Factorization (NMF), a randomized NMF was recently ... [more] |
MSS2022-105 NLP2022-150 pp.204-209 |
AI |
2022-07-04 14:10 |
Hokkaido |
(Primary: On-site, Secondary: Online) |
Data visualization analysis of factors influencing the recommendations of others in the service industry using an UMAP Fumiaki Saitoh (CIT) AI2022-9 |
Understanding the structure of customer segments is one of the important procedures in the scene of developing products ... [more] |
AI2022-9 pp.48-51 |
NLC, IPSJ-NL, SP, IPSJ-SLP [detail] |
2021-12-02 14:50 |
Online |
Online |
Music Separation by Regularized NMF using CQCC Kohei Miyajima, Makoto Ohki (Yamanashi Univ.) NLC2021-21 SP2021-42 |
In this paper, we propose a supervised music source separation method using acoustic features for music composed of mult... [more] |
NLC2021-21 SP2021-42 pp.17-21 |
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2021-06-28 14:15 |
Online |
Online |
Modification of Optimization Problem in Randomized NMF and Design of Optimization Method based on HALS Algorithm Takao Masuda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-4 IBISML2021-4 |
Nonnegative matrix factorization (NMF) is the process of decomposing a given nonnegative matrix into two nonnegative fac... [more] |
NC2021-4 IBISML2021-4 pp.23-30 |
EA, US, SP, SIP, IPSJ-SLP [detail] |
2021-03-04 10:15 |
Online |
Online |
A quantitative measure of discriminability between NMF dictionaries Eisuke Konno, Daisuke Saito, Nobuaki Minematsu (UTokyo) EA2020-82 SIP2020-113 SP2020-47 |
Supervised nonnegative matrix factorization (NMF) is a popular approach for monaural audio source separation. It realize... [more] |
EA2020-82 SIP2020-113 SP2020-47 pp.134-139 |
EA, ASJ-H |
2020-07-20 13:25 |
Online |
Online |
Multichannel NMF using cluster analysis and weighted average Tsuyoshi Yamamoto, Singo Uenohara, Kenichi Furuya (Oita Univ) EA2020-2 |
Herein, we propose a sound source separation method using multi-channel non-negative matrix factorization (MNMF). MNMF u... [more] |
EA2020-2 pp.7-12 |
NC, MBE (Joint) |
2020-03-05 14:40 |
Tokyo |
University of Electro Communications (Cancelled but technical report was issued) |
A method for sound source separation using the onset information based on the NMF with deformable bases Shota Uchida, Susumu Kuroyanagi (NITech) NC2019-98 |
Currently, the NMF with deformable bases has been proposed as a model for learning the sequences of frequency spectrum f... [more] |
NC2019-98 pp.131-136 |
EA, SIP, SP |
2019-03-14 13:30 |
Nagasaki |
i+Land nagasaki (Nagasaki-shi) |
[Poster Presentation]
An Initialization Method for Multichannel Nonnegative Matrix Factorization using Nonnegative Independent Component Analysis Takahiro Ushijima, Takanobu Uramoto, Shingo Uenohara, Ken'ichi Furuya (Oita Univ.) EA2018-105 SIP2018-111 SP2018-67 |
Recently, devices that handle voice have become widely used, and there is a demand for a technique to extract only the t... [more] |
EA2018-105 SIP2018-111 SP2018-67 pp.37-42 |
NLC, IPSJ-IFAT |
2019-02-08 10:20 |
Kyoto |
Ryukoku University Omiya Campus |
Inference of Local Feature Correlations and Detection of Structural Similarity for Text Data Keisuke Sasahara, Makoto Haraguchi (Hokkaido Univ.) NLC2018-44 |
We propose in this report methods for searching local correlations among features on text data and for detecting sentenc... [more] |
NLC2018-44 pp.47-52 |
IBISML |
2018-11-05 15:10 |
Hokkaido |
Hokkaido Citizens Activites Center (Kaderu 2.7) |
[Poster Presentation]
Variational Approximation Accuracy in Non-negative Matrix Factorization Naoki Hayashi (MSI) IBISML2018-51 |
The asymptotic behavior of the variational free energy of the non-negative matrix factorization (NMF) has been elucidate... [more] |
IBISML2018-51 pp.53-60 |
IEE-CMN, EMM, LOIS, IE, ITE-ME [detail] |
2018-09-27 15:15 |
Oita |
Beppu Int'l Convention Ctr. aka B-CON Plaza |
[Special Talk]
Coded Acquistion of Light Fields
-- From Basis Representation to Deep Learning -- Keita Takahashi (Nagoya Univ.) LOIS2018-15 IE2018-35 EMM2018-54 |
A light field, which is often understood as a set of dense multi-view images, has been utilized in various 2D/3D applica... [more] |
LOIS2018-15 IE2018-35 EMM2018-54 pp.29-30 |
SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 09:25 |
Okinawa |
|
Stable Estimation Method of Spatial Correlation Matrices for Multi-channel NMF Yuuki Tachioka (Denso IT Lab) EA2017-103 SIP2017-112 SP2017-86 |
Multi-channel non-negative matrix factorization (MNMF) achieves a high sound source separation performance but its initi... [more] |
EA2017-103 SIP2017-112 SP2017-86 pp.7-12 |
SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:00 |
Okinawa |
|
[Poster Presentation]
Sound Source Separation Using Supervised NMF Based on One-dimensional Oblique Projections Misaki Komatsu, Akira Tanaka (Hokkaido Univ.) EA2017-124 SIP2017-133 SP2017-107 |
In the conventional supervised NMF, mutual relationship between given
basis vectors is not considered appropriately, wh... [more] |
EA2017-124 SIP2017-133 SP2017-107 pp.133-134 |
SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:00 |
Okinawa |
|
[Poster Presentation]
Performance Evaluation of Initial Value Setting Method for Spatial Correlation Matrices in Multi-channel NMF Yu Tajima, Akira Tanaka (Hokkaido Univ.) EA2017-130 SIP2017-139 SP2017-113 |
The multi-channel nonnegative matrix factorization (MNMF) is an extension of the single-channel nonnegative matrix facto... [more] |
EA2017-130 SIP2017-139 SP2017-113 pp.161-162 |
EA |
2018-02-16 13:10 |
Hiroshima |
Pref. Univ. Hiroshima |
The effect of increasing the number of channels with multi-channel non-negative matrix factorization for noisy speech recognition Takanobu Uramoto (Oita Univ.), Youhei Okato, Toshiyuki Hanazawa (Mitsubishi Electric), Iori Miura, Shingo Uenohara, Ken'ich Furuya (Oita Univ.) EA2017-99 |
Nonnegative Matrix Factorization (NMF) factorizes a non-negative matrix into two non-negative matrices. In the field of ... [more] |
EA2017-99 pp.33-38 |
PRMU, MVE, IPSJ-CVIM [detail] |
2018-01-18 11:00 |
Osaka |
|
SVBRDF Acquisition Using Non-negative Matrix Factorization Tomoki Iwanaga (UTokyo), Yoshihiro Watanabe (UTokyo/JST), Masatoshi Ishikawa (UTokyo) PRMU2017-121 MVE2017-42 |
In this paper, we describe BRDF acquisition method using non-negative matrix factorization (NMF) aiming at fast BRDF mea... [more] |
PRMU2017-121 MVE2017-42 pp.81-86 |
WIT, SP |
2017-10-19 13:20 |
Fukuoka |
Tobata Library of Kyutech (Kitakyushu) |
Speech enhancement of utterance while playing with werewolf game "JINRO" based on NMF Shunsuke Kawano, Toru Takahashi (OSU) SP2017-35 WIT2017-31 |
We describe that speech enhancement for natural and multi speaker dialognue. To record natural and multi speaker dialogn... [more] |
SP2017-35 WIT2017-31 pp.7-12 |