ITE Technical Group Submission System
Conference Schedule
Online Proceedings
[Sign in]
    [Japanese] / [English] 
( Committee/Place/Topics  ) --Press->
 
( Paper Keywords:  /  Column:Title Auth. Affi. Abst. Keyword ) --Press->

All Technical Committee Conferences  (Searched in: All Years)

Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 7 of 7  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] 2022-02-22
16:30
Online online Relevance Analysis between Bio-signals of Engineers Inspecting Subway Tunnels and Their Inspection Behaviors
Kaito Hirasawa, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents relevance analysis between bio-signals of engineers inspecting subway tunnels and their inspection b... [more] MMS2022-32 ME2022-57 AIT2022-32
pp.365-370
AIT, ME, MMS, IEICE-IE, IEICE-ITS [detail] 2022-02-22
17:00
Online online A Note on Distress Detection based on Deep Learning with Hierarchical Multi-Scale Attention Mechanism for Supporting Maintenance of Subway Tunnels
Saya Takada, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
In maintenance of transportation infrastructures, advanced support technologies that can reduce the burden on engineers ... [more] MMS2022-34 ME2022-59 AIT2022-34
pp.377-381
IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2021-02-18
10:20
Online Online A Note on Improving Performance of Deep Learning-based Distress Detection for Supporting Maintenance of Subway Tunnels -- Accuracy Verification Focusing on Tunnel Wall Characteristics --
Tomoki Haruyama, Keisuke Maeda, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents the performance improvement of deep learning-based distress detection to support the maintenance of ... [more] MMS2021-1 ME2021-1 AIT2021-1
pp.1-6
IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2021-02-19
16:50
Online Online [Special Talk] Improving Efficiency of Hammering Inspection of Subway Tunnels based on Analyzing Inspection Data
Motoki Oyama, Yuki Wakuda, Maiku Abe (Hokkaido Univ.), Yukihiro Ishikawa, Yuki Enokidani, Daisuke Tanaka, Hideaki Yamaguchi (Tokyo Metro)
In this study, we aimed at optimizing the operation of the upper floor hammering sound inspection of the subway tunnel, ... [more] MMS2021-28 ME2021-28 AIT2021-28
pp.201-202
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-27
14:15
Hokkaido Hokkaido Univ.
(Cancelled)
A note on detection of distress regions in subway tunnels by using U-net based network
An Wang, Ren Togo, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ)
This paper presents an automated distress region detection method using subway tunnel images. We previously proposed a m... [more] MMS2020-14 HI2020-14 ME2020-42 AIT2020-14
pp.69-72
HI, IEICE-IE, IEICE-ITS, MMS, ME, AIT [detail] 2020-02-27
15:55
Hokkaido Hokkaido Univ.
(Cancelled)
A Note on Classification of Experienced and Novice Inspectors Based on Bio-signals While Inspecting in Subway Tunnels
Tetsuya Kushima, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents classification of experienced and novice inspectors based on bio-signals while inspecting in subway ... [more] MMS2020-20 HI2020-20 ME2020-48 AIT2020-20
pp.101-105
ME, IEICE-IE, IEICE-ITS, MMS, HI, AIT [detail] 2019-02-20
10:15
Hokkaido Hokkaido Univ. A note on estimation of inspectors' visual attention using distress images of subway tunnels -- Trial introduction of deep learning-based saliency prediction methods --
Ryota Saito, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents the first trial for estimating inspectors' visual attention of distress images in subway tunnels. Th... [more] MMS2019-30 HI2019-30 ME2019-52 AIT2019-30
pp.281-285
 Results 1 - 7 of 7  /   
Choose a download format for default settings. [NEW !!]
Text format pLaTeX format CSV format BibTeX format


[Return to Top Page]

[Return to ITE Web Page]


The Institute of Image Information and Television Engineers (ITE), Japan