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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
CCS, NLP 2022-06-09
17:15
Osaka
(Primary: On-site, Secondary: Online)
Visualization of decisions from CNN models trained on OpenStreetMap images labeled based on traffic accident data
Kaito Arase, Zhijian Wu, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2022-10 CCS2022-10
The authors have recently conducted training of Convolutional Neural Networks (CNNs) on OpenStreetMap images each of whi... [more] NLP2022-10 CCS2022-10
pp.46-51
CCS, NLP 2022-06-09
17:40
Osaka
(Primary: On-site, Secondary: Online)
Speeding up an algorithm for searching generalized Moore graphs
Taku Hirayama, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2022-11 CCS2022-11
Computer networks in data centers are modeled as undirected regular graphs, and the average shortest path length (ASPL) ... [more] NLP2022-11 CCS2022-11
pp.52-57
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
13:50
Online Online Simplification of Average Consensus Algorithm in Distributed HALS Algorithm for NMF
Keiju Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NC2021-3 IBISML2021-3
Nonnegative Matrix Factorization (NMF) is the process of approximating a given nonnegative matrix by the product of two ... [more] NC2021-3 IBISML2021-3
pp.15-22
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
NLP, MSS
(Joint)
2021-03-15
13:00
Online Online Proposal of Novel Distributed Learning Algorithms for Multi-Neural Networks
Kazuaki Harada, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2020-58
A method for multiple neural networks (NNs) with the same structure to learn multiple sets of training data collected at... [more] NLP2020-58
pp.17-22
NLP, MSS
(Joint)
2021-03-15
13:25
Online Online Graph Structure Optimization Using Genetic Algorithms
Hiroki Tajiri, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2020-59
There are many large and complex networks in the real world. These networks are modeled as graphs and analyzed using a v... [more] NLP2020-59
pp.23-28
MSS, CAS, IPSJ-AL [detail] 2020-11-25
16:35
Online Online Generalization of Pseudo-Decentralized Continuous-Time Algorithms for Estimation of Algebraic Connectivity
Katsuki Shimada, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2020-23 MSS2020-15
Development of decentralized algorithms for multiple agents in a network to estimate its connectivity is a fundamental a... [more] CAS2020-23 MSS2020-15
pp.22-27
MSS, CAS, IPSJ-AL [detail] 2020-11-25
17:00
Online Online Distributed Algorithms based on Multiplicative Update Rules for Nonnegative Matrix Factorization
Yohei Domen, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2020-24 MSS2020-16
Nonnegative matrix factorization (NMF) is a multivariate method that approximates a given nonnegative matrix by the prod... [more] CAS2020-24 MSS2020-16
pp.28-33
NLP 2020-05-15
13:00
Online Online A Genetic Algorithm for Minimizing Average Shortest Path Length of Regular Graphs
Reiji Hayashi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2020-3
For the problem of finding a regular graph with given order and degree that minimizes the average shortest path length, ... [more] NLP2020-3
pp.11-16
NLP 2020-05-15
13:25
Online Online Design of a Distributed Algorithm for Principal Component Analysis based on Power Method and Average Consensus
Mutsuki Oura, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2020-4
Principal component analysis is one of the most important methods of multivariate analysis, and has been applied in a wi... [more] NLP2020-4
pp.17-22
MSS, NLP
(Joint)
2020-03-09
09:50
Aichi  
(Cancelled but technical report was issued)
A Distributed Algorithm for Solving Sandberg-Willson Equations Based on Sequential Minimization of Convex Quadratic Functions
Masaaki Takeuchi, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2019-115
We propose a new distributed algorithm for multi-agent networks to solve Sandberg-Willson equations, which are well-know... [more] NLP2019-115
pp.13-18
MSS, NLP
(Joint)
2020-03-09
10:15
Aichi  
(Cancelled but technical report was issued)
A projected consensus-based algorithm for minimizing the maximum error of a system of linear equations with nonnegativity constraints
Kosuke Kawashima, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) NLP2019-116
If a system of linear equations with nonnegativity constraints has a solution then it can be considered as a constrained... [more] NLP2019-116
pp.19-23
PRMU, CNR 2018-02-19
09:30
Wakayama   Ellipsoid Fitting based on Geometric Distance for Real-time Human Pose Tracking
Takuya Kitamura, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ.) PRMU2017-149 CNR2017-27
 [more] PRMU2017-149 CNR2017-27
pp.25-30
PRMU, MVE, IPSJ-CVIM [detail] 2018-01-19
11:25
Osaka   3D Face Tracking and Modeling from Face Image Sequence
Ryuichi Saito, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ.) PRMU2017-136 MVE2017-57
 [more] PRMU2017-136 MVE2017-57
pp.229-234
PRMU, IPSJ-CVIM, IBISML [detail] 2016-09-05
09:30
Toyama   Real-time Human Pose Tracking Using Depth Sensor by Connected Sphere Model
Daiki Fukuyama, Tsuyoshi Migita, Shakunaga Takeshi (Okayama Univ.) PRMU2016-58 IBISML2016-13
Human pose tracking on a depth image sequence can be achieved by using a generative-model-based method, where a human bo... [more] PRMU2016-58 IBISML2016-13
pp.25-30
PRMU, BioX 2016-03-25
16:15
Tokyo   A Levenberg-Marquardt-Based Face Tracking Method with Shape Estimation in Real-Time
Kento Tsutsui, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ.) BioX2015-70 PRMU2015-193
A GPU-based Levenberg-Marquardt method can estimate 16 or more parameters in real-time, given an appropriate set of init... [more] BioX2015-70 PRMU2015-193
pp.173-178
PRMU, MVE, IPSJ-CVIM
(Joint) [detail]
2013-01-24
09:00
Kyoto   3d face tracking and recognition for depth image sensor
Soichiro Katayama, Hisayoshi Chugan, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ) PRMU2012-105 MVE2012-70
This paper discusses on face tracking and recognition when depth-image sensor is available. For the purpose, our image b... [more] PRMU2012-105 MVE2012-70
pp.199-204
PRMU, HIP 2010-03-15
15:35
Kagoshima Kagoshima Univ. Stereoscopic Reconstruction of Facial Shape with a Spline Surface
Yuta Nagai, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ.) PRMU2009-264 HIP2009-149
This paper describes a method for stereoscopic shape reconstruction that efficiently handles a smooth surface, such as a... [more] PRMU2009-264 HIP2009-149
pp.181-186
PRMU, HIP 2010-03-15
16:00
Kagoshima Kagoshima Univ. Recovery of Facial Shape based on Simultaneous Estimation of Shape, Reflectance Property and Light Position
Sachie Sawami, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ.) PRMU2009-265 HIP2009-150
This paper describes refinements of the previously reported method that simultaneously estimates shape, reflectance prop... [more] PRMU2009-265 HIP2009-150
pp.187-192
PRMU 2008-12-19
11:15
Kumamoto Kumamoto Univ. Efficient Sparse Template Tracking along with Directional Integral Matching
Toshiyuki Kuroda, Makoto Omori, Kenji Kodama, Tsuyoshi Migita, Takeshi Shakunaga (Okayama Univ.) PRMU2008-174
The sparse template condensation has been proposed by Matsubara and Shakunaga for efficient and robust object tracking.... [more] PRMU2008-174
pp.159-164
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