dbjapanメーリングリストアーカイブ（2019年）
[dbjapan] CFP(締切10/14): IEEE ISM Workshop MLCSA2019 (12/9-11, San Diego, California, USA)
- To: dbjapan [at] dbsj.org
- Subject: [dbjapan] CFP(締切10/14): IEEE ISM Workshop MLCSA2019 (12/9-11, San Diego, California, USA)
- From: 王 元元（Yuanyuan WANG） <y.wang [at] yamaguchi-u.ac.jp>
- Date: Tue, 1 Oct 2019 19:51:30 +0900
日本データベース学会の皆様
（重複して受け取られた場合はご容赦ください）
山口大学の王と申します。
お世話になっております。
今年12月にSan Diegoにて開催される国際会議IEEE ISM 2019の併設ワークショップ
MLCSA2019 (Machine Learning and Computing for Visual Semantic Analysis)
の論文募集のご案内をいたします。
機械学習、画像処理、ユビキタスコンピューティング、データマイニングなど
に関する論文を幅広く募集しております。
論文の投稿締切は ***10月14日*** となっており、
是非ともご投稿をご検討いただけますようよろしくお願いいたします。
* Workshop site: http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2019/index.html
* Submission link: https://easychair.org/conferences/?conf=mlcsa2019
* Submission deadline: October 14, 2019
どうぞよろしくお願い申し上げます。
*******************************************************************
MLCSA2019: IEEE ISM 2019 Workshop on Machine Learning and Computing for
Visual Semantic Analysis
San Diego, California, USA. December 9-11, 2019
http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2019/index.html
*******************************************************************
Recently, visual contents collected from surveillance cameras,
mobile phones, personal photo collections, news footage, or medical
images have been explosively increased. How to automatically/
quantitatively analyze and understand the acquired visual contents
is becoming one of the most active research areas in the vision
community due to the scientifically challenging problems and its
great benefits to real life applications. On the other hand, machine
learning techniques especially the deep learning framework have
manifested the surprising superiority for extracting structural and
semantic visual representation in numerous computer vision applications
such as image classification, object detection/localization, image
segmentation, captioning, and so on. With machine learning and
computing techniques, it is prospected to discover the inherent
structure of the available unconditioned visual contents and to
achieve more promising results for various applications based on
visual semantic analysis.
This workshop, on Machine Learning and Computing for Visual Semantic
Analysis (MLCSA2019) - aims at sharing latest progress and developments,
current challenges, and potential applications for exploiting large
amounts of visual contents.
++ List of Topics ++
===================================================================
The topics we are interested in, include constructing effective systems
to enable visual semantic analysis and building wide applications within
the fields of artificial intelligence, machine learning, image
processing,
ubiquitous computing, data mining, and others.
The topics of interest include, but are not limited to, the following:
- Unsupervised and semi-supervised learning
- Deep/transfer learning for image and multimedia analysis
- Statistical modeling of image processing task
- Spatio-temporal data mining
- Feature extraction and matching
- Activity/Pattern learning and recognition
- Application of visual semantic analysis
- Semantic analysis of surveillance image and video
- Remote sensing image understanding
- Big data management
- Medical data analysis
- Social data analysis
===================================================================
++ Important Dates ++
===================================================================
- Paper Submission: October 14, 2019, 11:59pm, PDT
- Acceptance Notification: October 25, 2019, PDT
- Camera-ready Submission: October 31, 2019, 11:59pm, PDT
- Workshop Date: to be announced
===================================================================
++ Submission Guidelines ++
(See http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2019/submission.html for
details)
===================================================================
Papers submitted to the MLCSA workshop must not have been previously
published and must not be currently under consideration for publication
elsewhere. We invite researchers and practitioners to submit papers
to the MLCSA workshop according to the guidelines available on the
conference website at https://www.ieee-ism.org/submission.
Only electronic submission will be accepted. The page numbers for
workshop papers are limited to 8, including all figures, tables, and
references. Paper authors MUST submit their manuscripts in PDF through
EasyChair conference submission system:
https://easychair.org/conferences/?conf=mlcsa2019
NOTE: Workshop papers allow up to 2 extra pages with $150 per extra
page.
These are hard deadlines; no extensions will be given.
===================================================================
++ Workshop Organizers++
===================================================================
- YongQing Sun (NTT, Japan)
- Xian-Hua Han (Yamaguchi University, Japan)
- YuanYuan Wang (Yamaguchi University, Japan)
===================================================================
++ Program Committee (Tentative)++
===================================================================
- Yen-Wei Chen (Ritsumeikan University, Japan)
- Wen-Huang Cheng (Academia Sinica, Taiwan)
- Basabi Chakraborty (Iwate Prefectural University, Japan)
- JunPing Deng (ShangHai Ocean University, China)
- Xin Fan (Dalian University of Technology, China)
- Yutaro Iwamoto (Ritsumeikan University, Japan)
- YanLi Ji (University of Electronic Science and Technology of China,
China)
- YuGang Jiang (Fudan University, China)
- Akisato Kimura (NTT Communication Science Laboratories, Japan)
- Xu Qiao (Shandong University, China)
- Jia Su (Capital Normal University, China)
- JianDe Sun (ShanDong Normal University, China)
- BoXin Shi (National Institute of Advanced Industrial Science and
Technology, Japan)
- Jian Wang (ShanDong Normal University, China)
===================================================================
（重複して受け取られた場合はご容赦ください）
山口大学の王と申します。
お世話になっております。
今年12月にSan Diegoにて開催される国際会議IEEE ISM 2019の併設ワークショップ
MLCSA2019 (Machine Learning and Computing for Visual Semantic Analysis)
の論文募集のご案内をいたします。
機械学習、画像処理、ユビキタスコンピューティング、データマイニングなど
に関する論文を幅広く募集しております。
論文の投稿締切は ***10月14日*** となっており、
是非ともご投稿をご検討いただけますようよろしくお願いいたします。
* Workshop site: http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2019/index.html
* Submission link: https://easychair.org/conferences/?conf=mlcsa2019
* Submission deadline: October 14, 2019
どうぞよろしくお願い申し上げます。
*******************************************************************
MLCSA2019: IEEE ISM 2019 Workshop on Machine Learning and Computing for
Visual Semantic Analysis
San Diego, California, USA. December 9-11, 2019
http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2019/index.html
*******************************************************************
Recently, visual contents collected from surveillance cameras,
mobile phones, personal photo collections, news footage, or medical
images have been explosively increased. How to automatically/
quantitatively analyze and understand the acquired visual contents
is becoming one of the most active research areas in the vision
community due to the scientifically challenging problems and its
great benefits to real life applications. On the other hand, machine
learning techniques especially the deep learning framework have
manifested the surprising superiority for extracting structural and
semantic visual representation in numerous computer vision applications
such as image classification, object detection/localization, image
segmentation, captioning, and so on. With machine learning and
computing techniques, it is prospected to discover the inherent
structure of the available unconditioned visual contents and to
achieve more promising results for various applications based on
visual semantic analysis.
This workshop, on Machine Learning and Computing for Visual Semantic
Analysis (MLCSA2019) - aims at sharing latest progress and developments,
current challenges, and potential applications for exploiting large
amounts of visual contents.
++ List of Topics ++
===================================================================
The topics we are interested in, include constructing effective systems
to enable visual semantic analysis and building wide applications within
the fields of artificial intelligence, machine learning, image
processing,
ubiquitous computing, data mining, and others.
The topics of interest include, but are not limited to, the following:
- Unsupervised and semi-supervised learning
- Deep/transfer learning for image and multimedia analysis
- Statistical modeling of image processing task
- Spatio-temporal data mining
- Feature extraction and matching
- Activity/Pattern learning and recognition
- Application of visual semantic analysis
- Semantic analysis of surveillance image and video
- Remote sensing image understanding
- Big data management
- Medical data analysis
- Social data analysis
===================================================================
++ Important Dates ++
===================================================================
- Paper Submission: October 14, 2019, 11:59pm, PDT
- Acceptance Notification: October 25, 2019, PDT
- Camera-ready Submission: October 31, 2019, 11:59pm, PDT
- Workshop Date: to be announced
===================================================================
++ Submission Guidelines ++
(See http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2019/submission.html for
details)
===================================================================
Papers submitted to the MLCSA workshop must not have been previously
published and must not be currently under consideration for publication
elsewhere. We invite researchers and practitioners to submit papers
to the MLCSA workshop according to the guidelines available on the
conference website at https://www.ieee-ism.org/submission.
Only electronic submission will be accepted. The page numbers for
workshop papers are limited to 8, including all figures, tables, and
references. Paper authors MUST submit their manuscripts in PDF through
EasyChair conference submission system:
https://easychair.org/conferences/?conf=mlcsa2019
NOTE: Workshop papers allow up to 2 extra pages with $150 per extra
page.
These are hard deadlines; no extensions will be given.
===================================================================
++ Workshop Organizers++
===================================================================
- YongQing Sun (NTT, Japan)
- Xian-Hua Han (Yamaguchi University, Japan)
- YuanYuan Wang (Yamaguchi University, Japan)
===================================================================
++ Program Committee (Tentative)++
===================================================================
- Yen-Wei Chen (Ritsumeikan University, Japan)
- Wen-Huang Cheng (Academia Sinica, Taiwan)
- Basabi Chakraborty (Iwate Prefectural University, Japan)
- JunPing Deng (ShangHai Ocean University, China)
- Xin Fan (Dalian University of Technology, China)
- Yutaro Iwamoto (Ritsumeikan University, Japan)
- YanLi Ji (University of Electronic Science and Technology of China,
China)
- YuGang Jiang (Fudan University, China)
- Akisato Kimura (NTT Communication Science Laboratories, Japan)
- Xu Qiao (Shandong University, China)
- Jia Su (Capital Normal University, China)
- JianDe Sun (ShanDong Normal University, China)
- BoXin Shi (National Institute of Advanced Industrial Science and
Technology, Japan)
- Jian Wang (ShanDong Normal University, China)
===================================================================
--
王 元元
山口大学大学院創成科学研究科
工学系学域・知能情報工学分野
（兼担：工学部知能情報工学科）
助教 博士（環境人間学）
0836-85-9522
Yuanyuan Wang, Ph.D
Assistant Professor, Department of Information Science and Engineering, College of Engineering,
Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Japan
E-mail: y.wang [at] yamaguchi-u.ac.jp