[Ieee_vis] Call for Papers: FITEE Special Issue on “AI for Visualization”

[jiazhi xia]

*Submission Deadline: July 31, 2019*

*Artificial intelligence (AI) technique*s, such as deep learning, have
achieved breakthrough in various tasks in recent years, such as computer
vision, natural language processing and speech recognition. The great
success of AI techniques has inspired a wide range of visualization
applications. First, while data transformation is one of the core steps in
visualization, recent embedding techniques and deep neural networks provide
new representations for complex data, disclosing latent features and
enabling efficient operations. Second, inspired by recent advances of
understanding visual contents in computer vision, researchers have begun to
introduce AI in visualization, such as data-driven quality metrics. Third,
while the main goal of visualization is to create new visual
representation, data-driven design has become a new methodology of
visualization generation. In addition, a great many of applications, such
as predictive visual analytics, have also been facilitated by recent AI
techniques.

Introducing recent AI techniques into visualization applications, however,
yields new methodological and practical challenges that need to be
addressed. First, unlike computer vision that can collect training data
conveniently, high-quality training data for specific visualization tasks
are scare. Second, visual contents in information visualization are rather
different from natural visual objects. The latter often have specific
contours and textures. Therefore, despite the high performance of deep
neural networks in understanding natural images and videos, there are still
debates on the applicability of deep neural networks in information
visualization. Third, well-formulated design spaces for specific
visualization suitable for vectorized representation of deep learning are
yet to be investigated. Finally, many tasks of visual analytics are
inherently interactive and progressive, integrating user interaction into
learning process is also a challenge.

For this special issue, we are looking for submissions that describe
algorithms, data representations, tools and systems for visualization tasks
based on AI techniques. We also welcome evaluations providing inspiring
guidelines on the use of AI techniques in visualization and surveys
providing comprehensive discussions on current development of "AI for VIS."
More specifically, we are looking for contributions that demonstrate
practical impact of AI on (but not limited to) the following topics:

*• Data synthesis for training of specific visualization tasks*

*• Data-driven quality metrics for visualization*

*• Data-driven design of visualization*

*• Deep learning model for visualization contents*

*• Interactive AI techniques for visual analytics*

*• Predictive visual analytics*

*To promote international cooperation, we encourage submissions that are
co-authored by domestic and international researchers. *We also highly
recommend the submission of multimedia to accompany each article as it may
significantly increase the visibility, downloads and citations.

All submitted manuscripts must be written in English and must not be under
consideration elsewhere for publication. The authors must follow the FITEE
guidelines (http://www.jzus.zju.edu.cn/manuscript.php) for preparation of
their manuscripts. Either Word or LaTeX format is acceptable. When Word is
used, please keep the layout of the text as simple as possible, e.g.,
single column, 1.5 lines spacing, 10.5 pt font size, and Times New Roman
font. When LaTeX is used, a template is available at
http://www.jzus.zju.edu.cn/download/FITEE_LaTex_template.zip

*Templates for accepted papers:*

Word: http://www.jzus.zju.edu.cn/download/FITEE_sample.doc

LaTeX: http://www.jzus.zju.edu.cn/download/FITEE_LaTex_template.zip

(At the initial submission stage, authors do not need to use these
templates. Only when asked to revise manuscripts after peer reviews, these
templates should be used.)

FITEE is an international peer-reviewed journal launched by the Chinese
Academy of Engineering (CAE) and Zhejiang University, and co-published by
Springer & Zhejiang University Press. FITEE aims to publish the latest
implementation of applications, principles, and algorithms in the broad
area of Electrical and Electronic Engineering.

All articles published in this special issue will be indexed by SCI-E and
will be available from http://www.springer.com/computer/journal/11714.
Please note that all articles will undergo international peer review and
Crosscheck processes before acceptance, to ensure that the special issue is
of high quality, original, and thought-provoking.

We look forward to your contribution to this special issue. Please send
your manuscript via http://www.editorialmanager.com/zusc/. Remember to
choose article type “S.I.-AI4VIS”.

*Manuscript submission by*

July 31, 2019

*Acceptance notification by*

Nov. 15, 2019

*Publication date:*

Jan. 31, 2020

*Editorial Board:*

*Editor-in-Chief:*

Prof. Yunhe Pan Academician of CAE, Zhejiang University, China

*Executive Lead Editor:*

Prof. Wei Chen CAD & CG State Key Lab, Zhejiang University, China

*Editors (in alphabetical order by last name):*

Prof. Steffen Koch University of Stuttgart, Germany

Prof. Tobias Schreck Graze University of Technology, Austria

Prof. Han-Wei Shen The Ohio State University, USA

Assoc. Prof. Jiazhi Xia Central South University, China

Dr. Cong Xie Facebook, USA

Prof. Ye Zhao Kent State University, USA

*For inquiries regarding this special issue, please contact:*

Jiazhi Xia

Central South University, China

E-mail: xiajiazhi at csu.edu.cn

Editorial Office:

Ziyang Zhai (Managing Editor)

jzus_zzy at zju.edu.cn

86-571-88273162



Best Regards,

Wei Chen

FITEE "AI for Visualization" Guest Editors
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