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IssuesSpecial Issues
Human-centric Computing and Information Sciences (HCIS) Korea Information Processing Society-Computer Software Research Group (KIPS-CSWG)(ISSN: 2192-1962)

(IF 5.900) Special issue on

Deep Video Analytics and Multimedia Services using Digital Twin

The Multimedia data has lot of emerging technology to handle the Business analytics Using Big Multi modal data and AI technique.The modern era has expansion of video data used for modern surveillance and personal data captures. The processing of large video data is indeed a big task. The deep learning based video data analytics is a major platform where most of the researchers focus on the big visual data to modern real time applications. The video data is assumed to be of holding a large spatial and temporal analysis which can be addressed easily with Deep learning to provide the clear pixel level labels with the AI based Deep video data analytics approaches. Besides, deep learning is an approach to solve supervised and unsupervised learning problem to address various issues arising due to GPU clusters.Digital Twin is a emerging topic that focuses mainly on the virtual objects that enhances the retrieval of the big multimedia data. The digital twin may enhance the fast retrieval of multimedia data with the support of deep learning algorithms. AI is a good technique to support the various perspectives with a wide range of capability from analysis to storage with good retrieval. The traditional infrastructures in data centres concentrates on the fast retrieval mechanism, but AI based HPC enables a supercomputing mechanism and flexible access with the support of various machine learning and deep learning algorithms. High Performance Computing (HPC) in association with Artificial intelligence based deep learning is often termed as deep Intelligent HPC, it drives a major shift in the paradigm with data analytics and subsequent data processing.


Topics of interest include, but are not limited to:


In this special issue, we aim to provide a forum for researchers with an interest in efficiency to examine challenging research questions, showcase the state-of-the-art, and share breakthroughs

Learning data representation from video based on supervised/unsupervised/semi-supervised learning using AI based Digital Twin

Deep learning on multi-modal social media disadvantage study - Quantitative multi-modal multimedia data analysis using Cloud based Digital Twinning

Data mining on big multi-modal social media networks using Cloud based AI using distributed analysis

Social behavior modelling, understanding, and patterns mining with deep models; - Smart cities using Cloud based AI using Digital Twin

IoT based Video Analytics using Cloud based AI using distributed analysis

Web video understanding using deep learning techniques, including classification, annotation, event detection and recognition, authoring and editing using Cloud based AI

Video highlights, summary and storyboard generation using Cloud based AI using distributed analysis

Digital Twin based Segmentation and tracking using Cloud based AI using distributed analysis

Data collections, benchmarking, and performance evaluation with Cloud based AI using distributed analysis

Human behavior analysis in real-time surveillance video surveillance using Cloud based AI

Important Dates

Open submission : 5 May 2021

Submission deadline : 30 October 2021

Author notification : within 4 weeks after submission

Revised manuscript due : within 2 weeks after notification

Notification of acceptance : within 2 weeks after revision submission

Tentative accepted paper publication date : within 2 months after final version

Tentative SI paper collection and its web open : 4th Quarter, 2021 or 1st Quarter, 2022

Submission Guideline

All submitted papers must be clearly written in excellent English and contain only original work. All papers must be submitted in an electronic format, e.g., PDF format (preferred) or MS Word. Manuscripts should follow the formatting of the sample manuscript and references. You can refer to the details in submission menu http://hcisj.com/submission/preparing_manuscript.php

All papers and some supplementary materials should be submitted through ScholarOne Manuscripts. The authors must select as “SI2021-01 Deep Video Analytics_Digital Twin”. when they reach the “Article Type” step in the submission process. https://mc04.manuscriptcentral.com/hcis and also for APC please refer http://hcisj.com/submission/article_processing_charges.php

Guest Editors

1. Dr.S.Vimal, Department of Computer Science and Engineering, Ramco Institute of Technology, Tamil Nadu, India
Email : vimal@ritrjpm.ac.in, svimalphd@gmail.com

2.Dr. Seifedine Kadry, Faculty of Applied Computing and Technology, Noroff University College, Kristiansand, Norway.
Email : seifedine.kadry@noroff.no

3.Dr. AlirezaSouri, Department of Computer Engineering, Haliç University, Beyoğlu, İstanbul, Turkey
Email : alirezasouri@halic.edu.tr

4.Dr. DaniloPelusi, Faculty of Communication Sciences,University of Teramo, Via Balzarini, 1, 64100, Teramo, Italy
Email : dpelusi@unite.it

5.Dr.Sitharthan R, School of electrical engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India.
Email : sitharthan.r@vit.ac.in