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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 47  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SS 2024-03-09
13:55
Okinawa
(Primary: On-site, Secondary: Online)
A Study on Cloud-Based Image Generation Using Spot Instances
Kippei Kasai, Daisuke Katayama, Takahiro Koita (Doshisha Univ.) SS2023-83
Recently, cloud computing has become an important service in the IT industry. However, there is a challenge for organiza... [more] SS2023-83
pp.202-206
SS 2023-03-15
16:45
Okinawa
(Primary: On-site, Secondary: Online)
Cost-performance evaluation of instances for execution of Scientific Workflows
Mitsuki Ogawa, Taichi Sugimura, Takahiro Koita (Doshisha Univ.) SS2022-73
The cloud environment is expected to be an ideal environment for scientific and technological computing workflows that a... [more] SS2022-73
pp.157-161
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
IN, NS
(Joint)
2023-03-02
12:50
Okinawa Okinawa Convention Centre + Online
(Primary: On-site, Secondary: Online)
Consideration of bidding method for spot instances on AWS regions
Kippei Kasai (Doshisha Univ.), Daisuke Katayama, Takahiro Koita (Grad.Sch.Engineering Doshisha Univ.) IN2022-74
One of the advantages of using the cloud is cost reduction, and AWS offers EC2, a virtual computing cloud, as spot insta... [more] IN2022-74
pp.51-56
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
MI 2022-07-08
14:00
Hokkaido
(Primary: On-site, Secondary: Online)
Cell type-specific tumor degree estimation in malignant lymphoma pathology images
Hiroki Masuda (NITech), Noriaki Hashimoto (RIKEN), Yusuke Takagi (NITech), Hiroyuki Hanada (RIKEN), Hiroaki Miyoshi, Kensaku Sato, Koichi Oshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (Nagoya Univ./RIKEN) MI2022-32
In the pathological diagnosis flow of malignant lymphoma, a type of blood cancer, it is important to identify the type o... [more] MI2022-32
pp.1-6
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-19
15:30
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Prognosis prediction for colorectal cancer from digitized pathological whole slide image using multiple instance learning
Kazuki Omori, Kenichi Morooka (Okayama Univ.), Ryota Nakanishi, Shoko Miyauchi, Eiji Oki, Tomoharu Yoshizumi (Kyushu Univ.) SIP2022-14 BioX2022-14 IE2022-14 MI2022-14
(To be available after the conference date) [more] SIP2022-14 BioX2022-14 IE2022-14 MI2022-14
pp.76-77
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
MI 2021-07-09
11:00
Online Online [Short Paper] Construction of Subtype Classifier for Malignant Lymphoma based on H&E-stained Images using Immuno-stainning Data
Yuki Hirono (NIT), Noriaki Hashimoto (RIKEN), Kugler Mauricio, Tatsuya Yokota (NIT), Miharu Nagaishi (Kurume Univ.), Hiroaki Miyoshi, Koichi Oshima (Kurume Univ./JSP), Ichiro Takeuchi (NIT/RIKEN), Hidekata Hontani (NIT) MI2021-16
In pathological diagnosis of malignant lymphoma, a HE image is observed at first and then a set of immunostained images ... [more] MI2021-16
pp.31-32
HCGSYMPO
(2nd)
2019-12-11
- 2019-12-13
Hiroshima Hiroshima-ken Joho Plaza (Hiroshima) Image Synthesis from Instance Map
Ryoka Oishi, Kyoko Sudo (Toho Univ.)
We propose a new network of image synthesis. The network generates multiple instances with variations from the semantic ... [more]
PRMU, MI, IPSJ-CVIM [detail] 2019-09-04
16:20
Okayama   Domain-adversarial multiple instance learning for subtype classification of malignant lymphoma
Daisuke Fukushima, Ryoichi Koga, Noriaki Hashimoto, Kaho Ko (Nagoya Inst. of Tech), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (Nagoya Univ. Hospital), Hidekata Hontani (Nagoya Inst of Tech), Ichiro Takeuchi (Nagoya Inst. of Tech/RIKEN/NIMS) PRMU2019-15 MI2019-34
We classify subtypes of malignant lymphoma using convolutional neural network with digital pathological images as input ... [more] PRMU2019-15 MI2019-34
pp.19-24
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
PRMU, IBISML, IPSJ-CVIM [detail] 2018-09-21
13:40
Fukuoka   Deployment Friendly Crack Detection via Convolutional Neural Network
Yuki Inoue, Shunsuke Ota, Hiroto Nagayoshi (Hitachi) PRMU2018-64 IBISML2018-41
Damage inspection, the first step in structural maintenance, is predominantly done manually today. Thus the cost of stru... [more] PRMU2018-64 IBISML2018-41
pp.201-206
SP 2018-08-27
11:00
Kyoto Kyoto Univ. Simple method for detecting GCI and GOI based on complex wavelet analysis with cosine series envelope
Hideki Kawahara (Wakayama Univ.), Ken-Ichi Sakakibara (Health Science Univ. Hokkaido) SP2018-22
We propose to use an analytic signal made from a cosine series envelope which was specially designed for analyzing the s... [more] SP2018-22
pp.1-5
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, IBISML, IPSJ-CVIM [detail] 2017-09-15
09:30
Tokyo   PRMU2017-43 IBISML2017-15 (To be available after the conference date) [more] PRMU2017-43 IBISML2017-15
pp.35-42
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-24
10:20
Okinawa Okinawa Institute of Science and Technology Risk Minimization Framework for Multiple Instance Learning from Positive and Unlabeled Bags
Han Bao (Univ. of Tokyo), Tomoya Sakai, Issei Sato (Univ. of Tokyo/RIKEN), Masashi Sugiyama (RIKEN/Univ. of Tokyo) IBISML2017-3
Multiple instance learning (MIL) is a variation of traditional supervised learning problems where data (referred to as b... [more] IBISML2017-3
pp.55-62
SIP 2015-08-20
13:25
Tokyo National Institute of informatics [Invited Talk] Introduction of TRECVID Instance Search Task and NII Approach
Shin'ichi Satoh (NII) SIP2015-60
Object retrieval in images and videos, especially instance search, is intended to retrieve specific objects such as comm... [more] SIP2015-60
p.49
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