[image 04801] [CfP] 論文募集(〆切: 9/16) 併設ワークショップ MLCSA @ ACCV'22, Dec. 4-8, in Macau, China

hanxhua hanxhua @ yamaguchi-u.ac.jp
2022年 8月 23日 (火) 10:45:06 JST

Image MLの皆様:


ACCV 2022 併設ワークショップの論文募集をご案内します。

[Apologies if you receive multiple copies of this CFP]
The Fourth Workshop on Machine Learning and Computing for Visual 
Semantic Analysis (MLCSA2022)
(In conjunction with ACCV 2022, Dec. 4-8, 2022, Macau, China)
Workshop website: http://mlp.sci.yamaguchi-u.ac.jp/MLCSA2022/index.html

Recently, explosive amount of visual content have been acquired with 
different kinds of visual sensors such as surveillance cameras, mobile 
phones, medical imaging equipment and remote sensors. The existing 
sensors may not always provide enough content or sufficient quality for 
different semantic analysis tasks. How to enhance the quality of the 
available visual data and reconstruct more additional information with 
computational technique such as hyper-spectral image reconstruction and 
high-speed video reconstruction from a snapshot have great affect for 
the subsequent vision tasks. Furthermore, the 
automatically/quantitatively analysis and understanding of the available 
visual data without sufficient quality 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 (MLCSA2022) – aims at sharing latest progress and developments, 
current challenges, and potential applications for exploiting large 
amounts of visual contents. We are interested in constructing effective 
systems to enable visual semantic analysis and building wide 
applications within the fields of artificial intelligence, machine 
learning, ubiquitous computing, data mining, and others.

TOPICS OF INTEREST (including but not limited to)
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 sample topics of interest include, but are not limited to, the 
•  Unsupervised and semi-supervised learning
•  Deep/transfer learning for image and multimedia analysis
•  Statistical modeling of image processing task
•  Image enhancement
•  Hyper-spectral image super-resolution/reconstruction
•  High-speed video reconstruction from compressive imaging snapshot
•  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
•  Medical data analysis

* Paper submission deadline: Sept. 16, 2022
* Acceptance notification: Sept. 30, 2022
* Camera-ready submission: Oct. 4, 2022


All submissions (including Work-In-Progress) must be original works not 
under review at any other workshop, conference, or journal. Submitted 
papers are limited to 14 pages, including figures and tables, in the 
ACCV style. Additional pages containing only cited references are 
allowed. Authors should consult Springer's authors'guidelines and use 
the above templates for the preparation of their papers. For more 
details, please check the submission guidelines in the workshop 


Advisory Committee
•  Prof. Yen-Wei Chen, Ritsumeikan University, Japan;
•   Prof. Shin'ichi Satoh, National Institute of Informatics, Japan

Names and contact information for main organizers:
•  Xian-Hua Han, Yamaguchi University, Japan
•  YongQing Sun, NTT, Japan;
•  Rahul Kumar JAIN, Ritsumeikan University, Japan

For more information, please visit the workshop website:  

E-mail: hanxhua @ yamaguchi-u.ac.jp
HP: http://mlp.sci.yamaguchi-u.ac.jp

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