2015 - Special Issue on Smart Computing for Large Scale Visual Data Sensing and Processing

Special Issue on Smart Computing for Large Scale Visual Data Sensing and Processing
Scope
Smart computing is an emerging multidisciplinary area, aiming to use computing technology to design smart methods, build smart systems, and make human life better. Visual signal plays the most important role in the communication and interaction between human and the surrounding world, while the past decade has witnessed the rapid development of digital imaging and transmission technologies. It is estimated that by 2015 the U.S. consumers will capture more than 100 billion digital pictures annually. In many practical vision applications, how to smartly collect the desired data and how to design smart algorithms to analyze the collected large amount of visual data have become very challenging issues. Meanwhile, the advancement of cloud computing, social computing, machine learning and artificial intelligence technologies are bringing smart computing to a newer dimension and improving our ways of living.
This special issue invites original papers on topics that are related to smart computing for large scale visual data sensing and processing. It provides an effective forum for researchers and engineers from a broad range of disciplines to exchange their creative ideas, share recent research advances, and identify future directions in response to grand challenges in intelligent computing technologies for large scale vision problems. This special issue will significantly benefit a large variety of audience from both academia and industry.
The topics of this special issue include, but are not limited to:
Visual data sensing and processing with new sensors
Large scale visual dataset benchmarking
High quality visual data reconstruction
Visual feature representation learning
Big visual data classification
Deep learning for vision applications
Vision applications for smartphone
Pervasive computing for vision
Cloud computing for vision
Active learning for visual data sensing and processing
Human in the loop for vision data processing
Multi-sensor visual data fusion
Internet based visual data exploration and computing
New computational architecture for large scale visual data processing
Papers will be evaluated based on their originality, presentation, and contribution to the field, as well as their relevance to the special issue. The submitted papers must be written in excellent English and describe original research which has not been published nor currently under review by other journals or conferences. Previously published conference papers should be clearly identified by the authors (at the submission stage) and an explanation should be provided how such papers have been extended to be considered for this special issue. Guest editors will make an initial determination of the suitability and scope of all submissions. Papers that either lack originality, clarity in presentation or fall outside the scope of the special issue will not be sent for review and the authors will be promptly informed in such cases.
Paper Submission
Papers can be submitted via the online submission system for Neurocomputing (http://ees.elsevier.com/neucom/ ). Preparation of the manuscript must follow the Guide for Authors which is available there.
Important Dates
Submission Deadline: Dec. 31, 2014
First Round Decisions: Mar. 31, 2015
Revisions Deadline: Apr. 30, 2015
Final Round Decisions: Jun. 30, 2015
Expected Online Publication: Sep. 2015
Guest Editors
Lei Zhang
Associate Professor, The Hong Kong Polytechnic University
http://www4.comp.polyu.edu.hk/~cslzhang/
Pinar Duygulu
Assistant Professor, Bilkent University
http://www.cs.bilkent.edu.tr/~duygulu/
Wangmeng Zuo
Associate Professor, Harbin Institute of Technology
http://homepage.hit.edu.cn/pages/wangmengzuo/4
Shiguang Shan
Professor, Institute of Computing Technology Chinese Academy of Sciences
http://vipl.ict.ac.cn/members/sgshan
Alex Hauptmann
Principal Systems Scientist, Carnegie Mellon University
http://www.cs.cmu.edu/~./alex/