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All Technical Committee Conferences (All Years)
| 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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