IEICE Technical Committee Submission System
Conference Schedule
Online Proceedings
[Sign in]
Tech. Rep. Archives
    [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 - 8 of 8  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
ITS, IEE-ITS 2023-03-13
16:20
Chiba Nihon Univ., Funabashi Campus
(Primary: On-site, Secondary: Online)
Prediction of the Future Location of a Vehicle captured from the Dashboard Camera using Instance Segmentation
Koki Ikeda, Takumi Uemura, Shuichi Ojima (Sojo Univ.) ITS2022-83
In recent years, the development of automated driving has been active in the automated driving industry, and Level 3 and... [more] ITS2022-83
pp.22-27
PRMU 2022-12-15
15:30
Toyama Toyama International Conference Center
(Primary: On-site, Secondary: Online)
Training Method for Image-based Instance Segmentation by Video-based Object-Centric Representation Learning
Tomokazu Kaneko, Ryosuke Sakai, Soma Shiraishi (NEC) PRMU2022-40
Object-centric representation learning (OCRL) aims to separate and extract object-wise representations from an image.
... [more]
PRMU2022-40
pp.43-48
PRMU, IPSJ-CVIM 2022-03-11
16:40
Online Online Extended Panel Detection and Pixel-Wise Segmentation for Comic Editing
Runtian Yu, Hikaru Ikuta, Yusuke Matsui, Kiyoharu Aizawa (UTokyo) PRMU2021-88
Comic panel extraction plays a significant role in various tasks such as comic editing. In this research, we first defin... [more] PRMU2021-88
pp.175-179
CQ, IMQ, MVE, IE
(Joint) [detail]
2022-03-09
09:45
Online Online (Zoom) Improving Weakly Supervised Instance Segmentation by Encoding Motion Information via Optical Flow
Jun Ikeda, Junichiro Mori (UT) IMQ2021-15 IE2021-77 MVE2021-44
Weakly supervised instance segmentation is an important task that can significantly reduce the annotation cost of model ... [more] IMQ2021-15 IE2021-77 MVE2021-44
pp.27-32
MVE 2021-09-17
14:30
Online Online Improving Mask Generation Accuracy Exploiting Optical Flow in Weakly Supervised Instance Segmentation
Jun Ikeda, Junichiro Mori (UTokyo) MVE2021-15
Weakly supervised instance segmentation is important because it reduces the huge pixel-level annotation cost required to... [more] MVE2021-15
pp.38-43
LOIS 2019-03-08
14:20
Okinawa Miyakojima-shi Central Community Center Examination of eye-camera image analysis method using Mask R-CNN
Yuto Yoshikawa, Yukikazu Murakami (NIT, Kagawa), Kazuaki Shiraishi, Gai Shibahara (NIT,Toba) LOIS2018-76
In recent years, opportunities for new farmers to receive direct guidance from experienced farmers have been decreasing ... [more] LOIS2018-76
pp.121-125
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
13:40
Okinawa   MI2017-78 Diseases appearing in the spine include spondylolysis, spondylolisthesis, vertebral fracture, and the like. A preoperati... [more] MI2017-78
pp.43-44
PRMU, MVE, IPSJ-CVIM
(Joint) [detail]
2013-01-23
11:10
Kyoto   Co-segmentation based on Multiple-Instance Learning
Jun Sakata, Toshikazu Wada (Wakayama Univ.) PRMU2012-90 MVE2012-55
Appearance learning of an object represented by a text can be realized by utilizing image retrieval systems on the Inter... [more] PRMU2012-90 MVE2012-55
pp.81-86
 Results 1 - 8 of 8  /   
Choose a download format for default settings. [NEW !!]
Text format pLaTeX format CSV format BibTeX format
Copyright and reproduction : All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)


[Return to Top Page]

[Return to IEICE Web Page]


The Institute of Electronics, Information and Communication Engineers (IEICE), Japan