Special Issue "Innovations in Artificial Intelligence using Data Mining and Big Data"

Submission Deadline: 30 November 2021
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Guest Editors
Dr. Mohammad Tabrez Quasim, University of Bisha, Saudi Arabia.
Dr. Surbhi Bhatia, King Faisal University, Saudi Arabia.
Prof. Swati Chandna, SRH University Heidelberg, Germany.

Summary

The two growing fields named as Data Mining and Big Data fascinate ideas and resources from varied disciplines along with machine learning, high computational techniques, and other statistical methods. The dynamic area combining different disciplines will help in extracting useful information for generating useful patterns with the aim of providing knowledge as a holistic view for diversified communities. Artificial Intelligence using data mining and big data theories with its applications will provide a comprehensive introduction to relevant innovations in the digital era and real-time applications. Artificial neural networks are a gross simplification of real networks of neurons. The paradigm of neural networks with data mining and big data could be a new and chop-chop growing field. The convergence will help in addressing the problems describing both theoretical and practical evaluations by directing useful knowledge with the power of Artificial Intelligence.


Keywords
Topics include but are not limited to:
Artificial Intelligence for Engineering Application
Machine Learning for Data Science
Soft Computing for Emerging Applications
Optimization Algorithms
Data Mining
Big Data Analytics
Opinion Mining
Deep Learning
Computational techniques

Published Papers
  • Fusion of Infrared and Visible Images Using Fuzzy Based Siamese Convolutional Network
  • Abstract Traditional techniques based on image fusion are arduous in integrating complementary or heterogeneous infrared (IR)/visible (VS) images. Dissimilarities in various kind of features in these images are vital to preserve in the single fused image. Hence, simultaneous preservation of both the aspects at the same time is a challenging task. However, most of the existing methods utilize the manual extraction of features; and manual complicated designing of fusion rules resulted in a blurry artifact in the fused image. Therefore, this study has proposed a hybrid algorithm for the integration of multi-features among two heterogeneous images. Firstly, fuzzification of two IR/VS… More
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