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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2020-01-30 10:00 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Construction of Basis Vectors for Representation of Immunostaining Combination by Non-negative Matrix Decomposition Kaho Ko, Noriaki Hashimoto, Tatsuya Yokota (NITech), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (NUH), Ichiro Takeuchi, Hidekata Hontani (NITech)  MI2019-99 |
In this paper, we propose a method that constructs a set of basis vectors for representing combination of immunostaining... [more] | MI2019-99 pp.151-154 |
| CQ, CBE (Joint) |
2020-01-17 14:00 |
Tokyo | NHK Science & Technology Research Laboratories | A study sound source separation method for recorded multiple sounds Satoru Jomae, Kenko Ota, Hideaki Yoshino (NIT) CQ2019-131 |
It is useful to separate multiple sounds into single sounds in order to improve the accuracy of fundamental frequency an... [more] | CQ2019-131 pp.137-140 |
| SIS | 2019-12-12 15:45 |
Okayama | Okayama University of Science | [Invited Talk]
Consensus-Based Distributed Algorithms and Applications to Machine Learning Norikazu Takahashi (Okayama Univ.) SIS2019-29 |
Recently, consensus-based distributed optimization methods for multi-agent systems have been vigorously studied in the f... [more] | SIS2019-29 p.35 |
| PRMU, MI, IPSJ-CVIM [detail] | 2019-09-05 10:35 |
Okayama | [Short Paper]
Dynamic PET Image Reconstruction using Non-Negative Matrix Decomposition with Deep Image Prior Tomoshige Shimomura, Kazuya Kawai (NIT), Muneyuki Sakata (Tokyo Metro. Inst. Gerontology), Yuichi Kimura (KU), Tatsuya Yokota, Hidekata Hontani (NIT) PRMU2019-24 MI2019-43 |
We present a PET image reconstruction method that can reconstruct dynamic PET images with high SN ratio and can simultan... [more] | PRMU2019-24 MI2019-43 pp.69-70 |
|
| CQ | 2019-07-18 13:00 |
Niigata | Niigata Univ. | [Poster Presentation]
A study of source separation method for non-negative matrix factorization using machine learning Satoru Jomae, Kenko Ota, Hideaki Yoshino (NIT) CQ2019-48 |
We proposed a sound source separation method which consists of Non-negative matrix factorization and deep neural network... [more] | CQ2019-48 pp.63-64 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-18 10:50 |
Okinawa | Okinawa Institute of Science and Technology | A sleep state analysis from calcium imaging data using non-negative matrix factorization Mizuo Nagayama, Toshimitsu Aritake (Waseda Univ.), Hideitsu Hino (ISM), Takeshi Kanda, Takehiro Miyazaki, Masashi Yanagisawa (Univ. of Tsukuba), Shotaro Akaho (AIST), Noboru Murata (Waseda Univ.) NC2019-14 IBISML2019-12 |
Sleep is an essential process for the survival of animals, however, its phenomenon is poorly understood. We aim to disco... [more] | NC2019-14 IBISML2019-12 pp.57-61(NC), pp.79-83(IBISML) |
| 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 |
| EA, SIP, SP | 2019-03-15 13:30 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | [Poster Presentation]
An Evaluation of Underdetermined Source Separation Based on Multichannel Variational Autoencoder Shogo Seki (Nagoya Univ.), Hirokazu Kameoka (NTT), Li Li (Univ. Tsukuba), Tomoki Toda, Kazuya Takeda (Nagoya Univ.) EA2018-154 SIP2018-160 SP2018-116 |
This paper deals with a multichannel audio source separation problem under underdetermined conditions. Multichannel Non-... [more] | EA2018-154 SIP2018-160 SP2018-116 pp.323-328 |
| OFT, OCS, OPE (Joint) [detail] |
2019-02-15 14:25 |
Fukuoka | Maximum and Minimum strain extraction from BGS observations including noise and optical loss using nonnegative matrix factorization Takuya Fujimoto, Hiroshi Naruse (Mie Univ.), Takanori Nishino (Meijo Univ.) OFT2018-81 OPE2018-210 |
We have proposed a method for extracting the maximum and minimum strains produced in a Brillouin gain spectrum (BGS) obs... [more] | OFT2018-81 OPE2018-210 pp.57-62(OFT), pp.89-94(OPE) |
|
| NLP, NC (Joint) |
2019-01-24 15:20 |
Hokkaido | The Centennial Hall, Hokkaido Univ. | A New Method for Deriving Multiplicative Update Rules for NMF with Error Functions Containing Logarithm Akihiro Koso, Norikazu Takahashi (Okayama Univ.) NLP2018-122 |
Nonnegative Matrix Factorization (NMF) is an operation that decomposes a given nonnegative matrix X into two nonnegative... [more] | NLP2018-122 pp.137-142 |
| CQ, ICM, NS, NV (Joint) |
2018-11-16 11:30 |
Ishikawa | Trend analysis method of operational data based on component decomposition using Non-negative Matrix Factorization Yuji Saitoh, Tetsuya Uchiumi, Yukihiro Watanabe (FUJITSU LAB.) ICM2018-32 |
In the ICT system, Understanding the trend of operational data such as the CPU usage rate is useful for system improveme... [more] | ICM2018-32 pp.45-50 |
|
| 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 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Recommendation for Market Places using Non-negative Matrix Factorization and MDL Priciple Yosuke Arano (Kyushu Univ.), Yusuke Miyake (GMO Pepabo), Masanori Kawakita, Junichi Takeuchi (Kyushu Univ.) IBISML2018-96 |
We apply the rank selection method for non-negative matrix factorization (NMF) based on MDL criterion which was propose... [more] |
IBISML2018-96 pp.389-395 |
| OFT | 2018-10-11 16:00 |
Miyagi | Touhoku Univ. | [Poster Presentation]
Maximum and Minimum strain extraction from Brillouin gain spectrum using nonnegative matrix factorization Takuya Fujimoto, Hiroshi Naruse (Mie Univ.), Takanori Nishino (Meijo Univ.) OFT2018-48 |
A fiber optic strain measurement based on the Brillouin scattering phenomenon enables a distributed strain measurement a... [more] | OFT2018-48 pp.157-161 |
| NLP | 2018-08-09 09:30 |
Kagawa | Saiwai-cho Campus, Kagawa Univ. | Derivation and Experimental Evaluation of a Novel Nonnegative Matrix Factorization Algorithm for Discovering Communities Yoshito Usuzaka, Norikazu Takahashi (Okayama Univ.) NLP2018-64 |
Community discovery is an important technique for a better understanding of the structure of a network. We consider the ... [more] | NLP2018-64 pp.57-62 |
| CAS, SIP, MSS, VLD | 2018-06-14 14:30 |
Hokkaido | Hokkaido Univ. (Frontier Research in Applied Sciences Build.) | New Matrix Factorization Method of DOSY for the Inhomogeneity Magnetic Field by using both the Eigenvalue Decomposition and the Approximation of the Diffusion Coefficient Yuho Tanaka, Kazunori Uruma (TUS), Tomoki Nakao (JEOL RESONANCE Inc.), Toshihiro Furukawa (TUS) CAS2018-9 VLD2018-12 SIP2018-29 MSS2018-9 |
Diffusion ordered 2D NMR spectroscopy (DOSY) estimates a diffusion coefficient and a spectrum by using nuclear magnetic ... [more] | CAS2018-9 VLD2018-12 SIP2018-29 MSS2018-9 pp.45-49 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 14:15 |
Okinawa | Okinawa Institute of Science and Technology | Data Analysis for Market Places by Non-negative Matrix Factorization and MDL Criterion Yosuke Arano (Kyushu Univ.), Yusuke Miyake (GMO Pepabo), Masanori Kawakita, Jun'ichi Takeuchi (Kyushu Univ.) IBISML2018-8 |
The rank selection method for non-negative matrix factorization (NMF) based on MDL criterion which was proposed by [Yama... [more] | IBISML2018-8 pp.53-60 |
| 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]
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 |
|
| MBE, NC (Joint) |
2018-03-13 10:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | Yuma Saito, Tsubasa Ito (Tokyo Tech), Keisuke Ota, Masanori Murayama (RIKEN), Toru Aonishi (Tokyo Tech) NC2017-68 |
Recent rapid progress of imaging techniques such as two-photon microscopes causes the extreme increase in amount of acqu... [more] | NC2017-68 pp.3-8 |
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