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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 21 - 40 of 115 [Previous]  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
LOIS, ICM 2022-01-27
15:25
Online Online [Invited Talk] Cyber Security with Human-in-the-Loop Machine Learning
Masato Uchida (Waseda Univ.) ICM2021-38 LOIS2021-36
There have been many studies on methods to detect various malicious activities in cyberspace using machine learning mode... [more] ICM2021-38 LOIS2021-36
pp.31-33
PRMU 2021-12-17
14:45
Online Online Data Selection for Efficient Deep Learning
Ryota Higashi, Toshikazu Wada (Wakayama Univ.) PRMU2021-51
We are investigating the method to sample the important data from the whole dataset for efficient training of Deep Neura... [more] PRMU2021-51
pp.148-153
PRMU 2021-12-17
15:40
Online Online [Short Paper] Segmentation of Cervical Cancer Pathological Image
Kengo Araki (Kyushu Univ.), Mariyo Rokutan-Kurata, Kazuhiro Terada, Akihiko Yoshizawa (Kyoto Univ.), Ryoma Bise (Kyushu Univ.) PRMU2021-55
(To be available after the conference date) [more] PRMU2021-55
pp.170-175
HCGSYMPO
(2nd)
2021-12-15
- 2021-12-17
Online Online Analysis of Eye Movements during Facial Attractiveness Evaluation based on Hidden Markov Model
Kazuyuki Asai, Shigeru Akamatsu (Hosei Univ.)
In this study, we analyzed whether there is a relationship between attractiveness evaluation for face images and eye mov... [more]
ET 2021-10-30
15:15
Online Online the relationship between proactive behavior at work and learning activity at university
Katsuhiko Ishikawa (YGU) ET2021-18
In this study, we examined the relationship between the possession of role models as learning behavior at university and... [more] ET2021-18
pp.13-18
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2021-06-28
15:45
Online Online Active learning for distributionally robust chance-constrained optimization
Yu Inatsu, Shion Takeno, Masayuki Karasuyama (Nitech), Ichiro Takeuchi (Nitech/RIKEN) NC2021-7 IBISML2021-7
Chance-constrained optimization (CCO) is one of the constrained optimization problems where some of the inputs to a blac... [more] NC2021-7 IBISML2021-7
pp.47-54
WIT 2021-06-01
14:30
Online Online An examination of interactive whiteboard for low vision that supports visual recognition of board information using laser retina imaging
Hisayuki Tatsumi, Noriyuki Horie (Tsukuba Univ. of Tech.), Yasuyuki Murai (Nihon Pharma. Univ.), Makoto Kobayashi (Tsukuba Univ. of Tech.) WIT2021-7
Of the two major visual behaviors for low vision students in school learning, reading a textbook is possible by bringing... [more] WIT2021-7
pp.32-37
HCS 2021-03-15
13:20
Online Online Trial effort to increase student participation in online class discussions -- Compare face-to-face and online classes --
Takashi Yamanaka (Kagawa Univ) HCS2020-70
Active involvement of students is indispensable for active learning that leads to deeper learning. In a class of about 4... [more] HCS2020-70
pp.18-20
MI 2021-03-15
15:30
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
pp.62-65
ET 2021-01-23
13:10
Online Online Implementation of AI chat bot into the interactive lecture module
Toshikazu Iitaka (Kumamoto Gakuen Univ.) ET2020-46
An AI chat bot function is implemented into the interactive lecture module which I have developed. The module implement... [more] ET2020-46
pp.1-6
LOIS 2020-03-12
11:05
Okinawa Nobumoto Ohama Memorial Hall
(Cancelled but technical report was issued)
Distributed active learning achieving both of monitoring and efficient time-series data sampling for edge computing
Osamu Saisho, Keiichiro Kashiwagi, Yui Saito, Tomoyuki Fujino (NTT) LOIS2019-73
For edge computing, there is still a great demand to upload only meaningful data to cloud,. However there is no practica... [more] LOIS2019-73
pp.97-101
ET 2020-03-07
10:35
Kagawa National Institute of Technology, Kagawa Collage
(Cancelled but technical report was issued)
A Proposal of an E-Portfolio-based System for Practice Problems to Foster Active Learning
Sayaka Sasaki, Yasuhiko Morimoto (Gakugei Univ.) ET2019-77
Personalized learning that supports each student’s learning adaptively based on his/her competencies is required in scho... [more] ET2019-77
pp.7-12
ET 2019-12-07
11:25
Tokyo Tokyo University of Agriculture and Technology Deterrence of Deterioration of Artifacts in the Hetero Pairing
Daisuke Ike, Kousuke Mouri, Keiichi Kaneko (TUAT) ET2019-61
In active learning, it is preferable to make learners group with different characteristics as much as possible. Learners... [more] ET2019-61
pp.17-20
SR 2019-12-05
13:50
Okinawa Ishigaki City Hall (Ishigaki Island) [Poster Presentation] Quality state analysis of eNodeB log data by semi-supervised learning using Self training
Shouta Yoshida (TCU), Atsushi Morohoshi (Fujitsu Fsas), Kohei Shiomoto (TCU), Chin Lam Eng, Sebastian Backstad (Ericsson Japan) SR2019-92
In an LTE network where traffic is increasing year by year. It is important to quickly find the cause when a failure occ... [more] SR2019-92
pp.29-36
ET 2019-10-19
15:30
Okinawa University of the Ryukyus An Interactive Robot Lecture for Changing Lecture Scenario
Ayumu Sugawara (UEC), Mitsuhiro Goto (NTT Service Evolutions Laboratories), Akihiro Kashihara (UEC) ET2019-44
In university lectures and e-Learning video lecture, it is important for lectures to change the order of lecture scenari... [more] ET2019-44
pp.69-74
IA 2019-10-04
16:00
Tokyo Tokyo Univ., Hongo Campus, Takeda Hall Active learning -- Student-centered presentation --
Taeko Oka (Human Environment Univ.) IA2019-20
(To be available after the conference date) [more] IA2019-20
pp.1-6
PRMU, MI, IPSJ-CVIM [detail] 2019-09-05
14:25
Okayama   Active learning based on self-supervised feature learning
Shunsuke Tsukatani, Kazuhiko Murasaki, Shingo Andou, jun Shimamura (NTT) PRMU2019-28 MI2019-47
In this paper, we propose an active learning algorithm based on self-supervised feature learning. When the domain of the... [more] PRMU2019-28 MI2019-47
pp.115-119
ET 2019-03-15
13:45
Tokushima Naruto University of Education Web contents for active learning of bookkeeping with creating duality forms -- -Development of teaching materials utilizing network- --
Tomohisa Mori (Matsushima H.S.), Osamu Akizuki (Miyagi Univ.) ET2018-92
In bookkeeping learning it is important to master the content of learning that carries out journals from transactions. L... [more] ET2018-92
pp.29-34
IMQ, IE, MVE, CQ
(Joint) [detail]
2019-03-14
15:10
Kagoshima Kagoshima University Reenactments of game-play styles in VR through personal bots -- Speculative visions for applications of attractiveness computing --
Taro Narahara (NJIT), Toshihiko Yamasaki (Univ. of Tokyo) IMQ2018-44 IE2018-128 MVE2018-75
Proposed educational modules demonstrate an AI’s ability to personalize things through re-enactments of robots assembled... [more] IMQ2018-44 IE2018-128 MVE2018-75
pp.127-130
SWIM 2019-02-22
16:00
Tokyo Kikai-Shinko--Kaikan Bldg. [Keynote Address] Attractiveness Computing based on Artificial Intelligence and Its Business Applications
Toshihiko YamasakiI (The University of Tokyo) SWIM2018-26
"Making my presentation more impressive," "Creating image/video content that can resonate well with consumers," "Attract... [more] SWIM2018-26
p.31
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