Proceedings of the International Conference on Computer Vision, High Performance Computing, Smart Devices and Networks

Dr. Ch. Satyanarayana  is currently working as Professor in the Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Kakinada, Andhra Pradesh, India. He received his Ph.D. in 2007 from JNTU. He has 20+ years of teaching, research experience, and 10 years of administrative experience in various capacities like Controller of Examinations, Head of the Department, and Director Academic and Planning. He has supervised 25 Ph.D. students and 200+ master’s students. He is Senior Member of IEEE. His research interests include image processing, speech recognition, pattern recognition, network security and big data analytics, and computational intelligence. Dr. Xiao-Zhi Gao received his B.Sc. and M.Sc. degrees from the Harbin Institute of Technology, China, in 1993 and 1996, respectively. He obtained his D.Sc. (Tech.) degree from the Helsinki University of Technology (now Aalto University), Finland, in 1999. In January 2004, he was appointed as Docent (Adjunct Professor) at the same university. He is now working as Professor of data science at the University of Eastern Finland, Finland. He is also Guest Professor at the Harbin Institute of Technology, Beijing Normal University, and Shanghai Maritime University, China. He has published more than 400 technical papers on refereed journals and international conferences, and his current Google Scholar H-index is 32. His research interests are nature-inspired computing methods (e.g., neural networks, fuzzy logic, evolutionary computing, swarm intelligence, and artificial immune systems) with their applications in optimization, data mining, machine learning, control, signal processing, and industrial electronics. Dr. Choo-Yee Ting is currently working as Professor at the Faculty of Computing and Informatics, Multimedia University, Cyberjaya, Malaysia. He is also Deputy Dean of the Institute for Postgraduate Studies, Multimedia University. In year 2002, he was awardedFellow of Microsoft Research by Microsoft Research Asia, Beijing, China. He has been active in research projects related to predictive analytics and big data. Most of the projects were funded by MOE, MOSTI, Telekom Malaysia, MDeC, and industries. In year 2014, he and his team members won two national-level big data analytics competitions. He has been Trainer for MDeC and INTAN for courses related to big data and data science. He is also Consultant, Mentor, and Assessor for projects under MDeC funding. Currently, he is working on Trouble Ticket Resolution prediction for Telekom Malaysia, AirAsia seat capacity optimization, and Dengue outbreak prediction for the government of Philippines. He is certified in Microsoft Technology Associate (Database), IBM DB2 CDA, and the Coursera Data Science Specialization (John Hopkins University). Dr. Naresh Babu Muppalaneni is currently working as Assistant Professor in the Department of Computer Science and Engineering at the National Institute of Technology, Silchar. He received his M.Tech. from Andhra University and Ph.D. from Acharya Nagarjuna University. He has published more than 30 papers in different International journals, chapters, and conference proceedings and edited research volumes. He has published 5 volumes in Springer Briefs in Forensic and Medical Bioinformatics. He is Fellow of IETE, Life Member of CSI, Member of ISCA, and Senior Member of IEEE. He is Recipient of Best Teacher Award from JNTU Kakinada. He has completed research projects worth of 2 crore rupees from DST, DRDO. He has organized 6 international conferences and 4 workshops. His research interests are artificial intelligence in biomedical engineering, human and machine interaction and applications of intelligent system techniques, social network analysis computational systems biology, bioinformatics, and cryptography ​

Character Recognition System using CNN For Sanskrit Text.- Resampling Imbalanced Data and Impact of Attribute Selection Methods in High Dimensional Data.- Wireless sEMG Acquisition and Monitoring- A Survey.- Black Hole Algorithm for Bigdata Anonymization.- Sleep Quality Analysis using Motion Signals and Heart Rate.- Prediction and Performance Assessment in Woman Handball Athletes by Employing Machine Learning Methods.- Adaptive Sparse K-Means and Optimization Enabled Neural Network from Gene-Expression Data for Cancer Classification.- Deep Learning for Object Detection: A Survey Routing Protocols: A Survey.- Performance Evaluation of Segmentation Algorithms in Non Contrast and Contrast MRI Images for Region of Interest.