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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 13 of 13  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2021-03-15
Online Online Evaluation of Bayesian Active Learning for Segmentation of Liver and Spleen in Large Scale Abdominal MR Data Sets
Bin Zhang, Yoshito Otake, Mazen Soufi (NAIST), Masatoshi Hori (Kobe University), Noriyuki Tomiyama (Osaka University), Yoshinobu Sato (NAIST) MI2020-60
Manual annotation in image segmentation is time-consuming and expensive. In order to obtain large number of annotated da... [more] MI2020-60
MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] 2020-05-28
Online Online [Special Talk] Generalization of coherent point drift and its acceleration
Osamu Hirose (Kanazawa Univ.) SIP2020-1 BioX2020-1 IE2020-1 MI2020-1
Point set registration is to find point-to-point correspondences between point sets, each of which represents the shape ... [more] SIP2020-1 BioX2020-1 IE2020-1 MI2020-1
R 2019-12-13
Tokyo Kikai-Shinko-Kaikan Bldg. Statistical method of estimating the date when school lunch caused mass food poisoning was supplied
Mitsuhiro Kimura (Hosei Univ.), Shuhei Ota (Kanagawa Univ.) R2019-51
We focus on estimating the date when school lunch caused mass food poisoning was supplied. In the literature, a log-norm... [more] R2019-51
ISEC, SITE, ICSS, EMM, HWS, BioX, IPSJ-CSEC, IPSJ-SPT [detail] 2019-07-24
Kochi Kochi University of Technology Stochastic Existence Connecting Logos that are not necessarily completely divided and Language Games -- Limitations of Security Models and the Possibility of Artificial Intelligence --
Tetsuya Morizumi (KU) ISEC2019-49 SITE2019-43 BioX2019-41 HWS2019-44 ICSS2019-47 EMM2019-52
In this paper we describe that AI architecture including input data in artificial intelligence system for Bayesian estim... [more] ISEC2019-49 SITE2019-43 BioX2019-41 HWS2019-44 ICSS2019-47 EMM2019-52
Okinawa OKINAWA ZANPAMISAKI ROYAL HOTEL Reconstruction of Virtual Network by Bayesian Attractor Model
Tatsuya Otoshi, Yuichi Ohshita, Masayuki Murata (Osaka Univ.) IN2016-129
Network Virtualization is expected to handle the various network traffic induced by such as IoT applications because a v... [more] IN2016-129
ICSS 2014-11-28
Miyagi Tohoku Gakuin University (Tagajo Campus) searching malicious URL from vast webspace
Bo Sun (Waseda Univ.), Mitsuaki Akiyama, Takeshi Yagi (NTT), Tatsuya Mori (Waseda Univ.) ICSS2014-61
Many Web-based attacks such as Drive-by-download and phishing scam
are easily triggered by accessing landing page URL.... [more]
IBISML 2013-11-12
Tokyo Tokyo Institute of Technology, Kuramae-Kaikan [Poster Presentation] Performance Comparisons between Dependency Networks and Bayesian Networks
Kazuya Takabatake, Shotaro Akaho (AIST) IBISML2013-41
Dependency networks are graphical models in which tasks of learning are done by totally local and simple algorithms of i... [more] IBISML2013-41
IBISML 2011-11-09
Nara Nara Womens Univ. An Extension of Probabilistic PCA for Correlated Samples
Kohei Hayashi (NAIST), Masanori Kawakita (Kyushu Univ), Kazushi Ikeda (NAIST) IBISML2011-50
Principal component analysis (PCA) is one of dimensional reduction methods and has widely been used for feature extracti... [more] IBISML2011-50
IBISML 2011-11-10
Nara Nara Womens Univ. Sequential Network Change Detection with Its Applications to Advertisement Impact Relation Analysis
Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-71
This paper addresses the issue of network change detection from non-stationary time series data. We employ as a represen... [more] IBISML2011-71
IBISML 2011-06-20
Tokyo Takeda Hall Network Change Detection with Its Applications to Advertisement Impact Relation Analysis
Yu Hayashi, Kenji Yamanishi (Univ. of Tokyo.) IBISML2011-9
This paper addresses the issue of network change detection with its applications to advertisement impact relation analys... [more] IBISML2011-9
MBE 2010-10-14
Osaka Osaka Electro-Communication University Sequential Error Rate Evaluation of EEG:SSVEP Binary Classification Problem -- Bayesian Sequential Learning with Sequential Monte Carlo method --
Hideyuki Hara (Waseda Univ.), Atsushi Takemoto (Kyoto Univ.), Yumi Dobashi (Waseda Univ.), Katsuki Nakamura (Kyoto Univ.), Takashi Matsumoto (Waseda Univ.) MBE2010-31
An attempt was made to evaluate the \textit{Sequential Error Rate} (SER) of an SSVEP classification problem with a Bayes... [more] MBE2010-31
USN, IPSJ-UBI 2009-07-16
Kyoto ATR (Kyoto) Applying a Probabilistic Inference Stream Processing Engine to a Camera Sensor Network
Ryo Sato, Hideyuki Kawashima, Hiroyuki Kitagawa (Univ. of Tsukuba) USN2009-20
The purpose of this paper is to appropriately incorporate Bayesian networks into a relational stream processing
system ... [more]
PRMU, NLC, TL 2006-10-20
Tokyo   Lawn weeds detection methods using image processing techniques
Ukrit Watchareeruetai, Yoshinori Takeuchi, Tetsuya Matsumoto, Hiroaki Kudo, Noboru Ohnishi (Nagoya Univ.)
In this work, three methods of lawn weeds detection based on various image processing techniques, Bayesian classifier, m... [more] PRMU2006-115
 Results 1 - 13 of 13  /   
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