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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 32  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2022-07-08
16:00
Hokkaido
(Primary: On-site, Secondary: Online)
[Short Paper] Unsupervised Domain Adaptation for Liver Tumor Detection in Multi-Phase CT images Using Adversarial Learning with Maximum Square Loss
Rahul Kumar Jain (Rahul), Takahiro Sato (Takahiro), Taro Watasue (Taro), Tomohiro Nakagawa (Tomohiro), Yutaro Iwamoto (Yutaro), Xianhua Han (Xianhua), Lanfen Lin (Lanfen), Hongjie Hu (Hongjie), Yen-Wei Chen (Yen-Wei) MI2022-37
(To be available after the conference date) [more] MI2022-37
pp.22-23
MI 2022-07-08
16:20
Hokkaido
(Primary: On-site, Secondary: Online)
[Short Paper] Multi-phase CT Image Segmentation with Single-Phase Annotation Using Adversarial Unsupervised Domain Adaptation
Swathi Ananda (Swathi), Yutaro Iwamoto (Yutaro), Xianhua HAN (Xianhua), Lanfen Lin (Lanfen), Hongjie Hu (Hongjie), Yen-Wei Chen (Yen-Wei) MI2022-38
(To be available after the conference date) [more] MI2022-38
pp.24-25
MI 2022-01-26
14:05
Online Online [Short Paper] Joint Learning for Multi-Phase CT Image Registration and Automatic Recognition of Anatomical Structures Based on a Deep Neural Network
Ryotaro Fuwa, Xiangrong Zhou, Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2021-64
Computer-aided diagnosis (CAD) systems require image registration and automatic recognition of anatomical structures on ... [more] MI2021-64
pp.82-85
MI 2022-01-26
15:00
Online Online [Special Talk] TBA
Ryoma Bise (Kyushu Univ.) MI2021-66
Supervised learning (e.g., deep learning) has been used for various tasks in biomedical image analysis. While supervised... [more] MI2021-66
p.88
KBSE, IPSJ-SE, SS [detail] 2021-07-08
15:40
Online Online (Zoom) A Study of the Fruit Sorting System Using YOLO Object Detection
Hiroyuki Akai, Mengchun Xie, Mitsutoshi Murata, Nobuo Iwasaki, Toru Mori (NIT, Wakayama College) SS2021-8 KBSE2021-20
Recently, the development of systems for agriculture using deep learning has been progressing. When applying deep learni... [more] SS2021-8 KBSE2021-20
pp.41-45
MI 2021-03-16
16:15
Online Online Pre-operative Head CT and Pathological Image Registration using Normalized Cross-Correlation and Dice coefficient
Yukinobu Matsuoka, Kento Morita (Mie Univ.), Daisuke Takeda, Takumi Hasegawa (Kobe Univ. Hospital), Tetsushi Wakabayashi (Mie Univ.) MI2020-81
The radiation therapy to oral cancer sometimes causes the osteoradionecrosis of jaws which is know as a refractory disea... [more] MI2020-81
pp.144-149
SeMI 2021-01-20
14:50
Online Online SeMI2020-48 Although Convolutional Neural Network (CNN) showed high potential for automatic meter reading, it is facing various chal... [more] SeMI2020-48
pp.27-32
MICT, MI 2018-11-06
16:40
Hyogo University of Hyogo [Short Paper]
Matsuzaki Hiroki, Yamada Atsushi, Takeda Iori, Mizutani Hiroya (Univ. of Tokyo), Ono Toshitsugu (Tokyo Univ.), Koike Kazuhiko, Ushiku Yoshitaka, Naganuma Kazunori, Onodera Hiroshi (Univ. of Tokyo) MICT2018-53 MI2018-53
The endoscopic biopsy specimen of the gastrointestinal tract is made transparent, and the tumor is detected by deep lear... [more] MICT2018-53 MI2018-53
pp.65-66
MVE, IE, CQ, IMQ
(Joint) [detail]
2017-03-07
09:30
Fukuoka Kyusyu Univ. Ohashi Campus *
Masahiro Shida, Yoshinari Kameda (Univ. of Tsukuba), Yuka Ishiduka (Keio Univ.), Airi Tsuji (Univ. of Tsukuba), Takuya Enomoto, Junichi Yamamoto (Keio Univ.), Kenji Suzuki, Itaru Kitahara (Univ. of Tsukuba) IMQ2016-39 IE2016-154 MVE2016-62
(To be available after the conference date) [more] IMQ2016-39 IE2016-154 MVE2016-62
pp.107-112
ET 2014-06-14
14:30
Shizuoka Shizuoka Univ. (Hamamatsu Campus) Development and evaluation of white board lecture video interface
Satoshi Shimada (Nippon Univ.) ET2014-16
Tacit knowledge of experts is expressed by instructional presentations in the course of daily instruction. This paper de... [more] ET2014-16
pp.45-50
PRMU, CNR 2014-02-13
15:30
Fukuoka   A Digital Annotation Sharing System for Poster Sessions
Katsuma Tanaka, Kai Kunze, Motoi Iwata, Masakazu Iwamura, Koichi Kise (Osaka Prefecture Univ.) PRMU2013-136 CNR2013-44
In this paper we describe a novel annotation sharing system which is capable of seamlessly linking physical and digital ... [more] PRMU2013-136 CNR2013-44
pp.83-88
PRMU, IBISML, IPSJ-CVIM [detail] 2013-09-03
16:15
Tottori   Image annotation from wild using semantic hierarchies
Masatoshi Hidaka, Naoyuki Gunji, Tatsuya Harada (Univ. of Tokyo) PRMU2013-52 IBISML2013-32
For many-class image annotation system, automatic construction of large-scale dataset is needed. Wild web is regarded as... [more] PRMU2013-52 IBISML2013-32
pp.201-206
PRMU, MI, IE 2013-05-24
11:00
Aichi   Measurement of Image Instance-based Distance between Concepts using Adaptive Visual Feature Selection
Kazuaki Nakamura, Ayaka Otoshi, Noboru Babaguchi (Osaka Univ.) IE2013-10 PRMU2013-3 MI2013-3
In recent years, measurement methods for similarity or distance between concepts have got more and more attention due to... [more] IE2013-10 PRMU2013-3 MI2013-3
pp.13-18
PRMU 2013-03-14
17:30
Tokyo   Automatic Generation of Subjective Sentence from Image for Social Networking and Micro-blog Services
Hiroko Kobayashi, Nobuhiro Fujinawa, Hidenori Kuribayashi, Toyoharu Sasaki, Takeshi Matsuo, Shinichi Nakajima (Nikon) PRMU2012-203
Generating sentences from a given image is becoming an active area of research. Obtaining sentences
that objectively de... [more]
PRMU2012-203
pp.135-139
PRMU, IBISML, IPSJ-CVIM
(Joint) [detail]
2012-09-03
10:30
Tokyo   Nonparametric Bayesian Estimation for Automatic Image Annotation Using Gaussian Mixture Model
Yukihiro Tsuboshita, Noriji Kato (Fuji Xerox), Masato Okada (The universisty of Tokyo) PRMU2012-40 IBISML2012-23
Automatic image annotation (AIA) is a process to automatically assign metadata to a digital image in the form of caption... [more] PRMU2012-40 IBISML2012-23
pp.93-98
ICM 2012-07-13
10:55
Hokkaido   An image-based annotation technique to overlay users' knowledge on existing systems
Yuto Kawabata, Takeshi Masuda, Ikuya Takahashi (NTT)
We propose an interactive annotation system that allows users to obtain operational knowledge from information overlaid ... [more]
PRMU, FM 2011-12-16
16:00
Shizuoka Hamamatsu Campus, Shizuoka Univ. Image Annotation Using Adapted Gaussian Mixture Model
Yukihiro Tsuboshita, Noriji Kato (Fuji Xerox), Masato Okada (The Univ. of Tokyo) PRMU2011-144
In the present study, we focus on learning based automatic image annotation method using Gaussian mixture model (GMM) as... [more] PRMU2011-144
pp.113-118
PRMU, IBISML, IPSJ-CVIM [detail] 2011-09-06
15:50
Hokkaido   Improvement image annotation using geo information and image composition
Naoyuki Abe, Atsushi Shimada, Hajime Nagahara, Rin-ichiro Taniguchi (Kyushu Univ.) PRMU2011-82 IBISML2011-41
In recent years, many researchers use collective intelligence of the web to study an image annotation problem. The image... [more] PRMU2011-82 IBISML2011-41
pp.195-200
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] 2011-02-21
13:15
Hokkaido Hokkaido University A note on keyword hierarchy construction using visual features and its application to image annotation
Marie Katsurai, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) ITS2010-35 IE2010-110
This paper proposes a keyword hierarchy construction method and its application to automatic image annotation. This meth... [more] ITS2010-35 IE2010-110
pp.69-72
PRMU 2011-02-17
10:00
Saitama   Large Scale Image Classification using Metric based on Correlation between Multiple Image Features and Class Labels
Yoshitaka Ushiku, Yuya Yamashita, Jun Imura, Hideki Nakayama, Tatsuya Harada, Yasuo Kuniyoshi (Tokyo Univ.) PRMU2010-208
In this paper, we propose a scalable image recognition method for both image classification and image annotation. We fir... [more] PRMU2010-208
pp.1-6
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