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Multimedia Tools and Applications 2015 : Special Issue on Big Image Processing and Analytics in Multimedia Tools and Applications


When N/A
Where N/A
Submission Deadline Feb 28, 2015
Notification Due Apr 30, 2015
Final Version Due Jun 30, 2015
Categories    big data   image processing   multimedia

Call For Papers

Special Issue on Big Image Processing and Analytics in Multimedia Tools and Applications

Currently, with the explosion of multimedia data (image, video and audio) from remote sensors, mobile image captures, social sharing, the web, TV shows and movies, huge volume of images are being generated and consumed daily. The availability of massive images has created fundamental challenges to image processing and analysis. Big Data is a term used to refer to massive and complex datasets made up of a variety of data structures, including structured, semi-structured, and unstructured data. Today, businesses are aware that big data can be used to generate new opportunities and process improvements through their processing and analysis. The emergence of big data has brought about a paradigm shift to many fields of computing. We have seen remarkable advances in computing power and storage capacity of big data management. But most big data systems currently in use handle data types of text or numbers. Novel and scalable data management and analytical frameworks are needed to meet the challenges posed by the big images.
The purpose of this special issue is to seek high quality research papers that contribute to the advancement of knowledge in big image processing and analysis. Researchers and practitioners are invited to submit original papers addressing topics including but not limited to the following:
 Scalable algorithms for image data mining
 Novel indexing methods for massive image data
 NoSQL solutions for big image data
 Visualization of massive images
 Classification and annotation of massive images
 Content-based and key-based massive image retrieval
 Semantic retrieval of massive images
 Customizations and extensions of existing software infrastructures such as Hadoop for image data management and analysis
 Applications of big image retrieval and analysis

Submission Guidelines
Authors are encouraged to submit high quality, original work that has neither appeared in, nor is under consideration by, other journals. Manuscripts based on previously published conference papers must be extended substantially. All manuscripts will undergo the same rigorous Multimedia Tools and Applications review process. Manuscripts should be submitted to: Please choose “Big Image Processing and Analytics” as the Article Type.

Important Dates
Paper submission: February 28, 2015
Review results to authors: April 30, 2015
Revised paper submission: May 31, 2015
Final acceptance notification: June 30, 2015
Final Papers Due: July 31, 2015

Guest Editors
Zongmin Ma, Ph.D. & Professor
College of Information Science and Engineering
Northeastern University, Shenyang, China
Rafal A. Angryk, Ph.D. & Associate Professor
Department of Computer Science
Georgia State University, Atlanta, USA
Sanggil Kang, Ph.D. & Associate Professor
Department of Computer and Information Engineering
Inha University, Inchon, Korea

Related Resources

SI: CAfBMD 2016   Springer Multimedia Tools and Applications Special Issue on Content Analysis for Big Multimedia Data
IJE 2016   International Journal of Education
ICCV 2017   International Conference on Computer Vision
ICSIPA 2017   IEEE International Conference on Signal and Image Processing Applications
ICWOC 2017   5th International Conference on Wireless and Optical Communications-Scopus, Ei Compendex
IEEE BigComp 2017   [Deadline Extension Oct 21, 2016] 2017 IEEE International Conference on Big Data and Smart Computing
ICSIP-IEEE 2017   2nd International Conference on Signal and Image Processing - IEEE
ICMR 2017   ACM International Conference on Multimedia Retrieval
QoMEX 2017   Quality of Multimedia Experience
ESANN 2017   25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning