Call For Papers

MIND-2021 will be held in virtual mode. Original contributions are invited from prospective authors with interests in the indicated conference topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period. The papers can be theoretical, practical and application oriented on the conference tracks. Every submission must identify the conference track which best relates to the contents of the paper. Papers will be peer reviewed by the International Program Committee, and may be accepted for long and short presentation. All the peer reviewed and selected papers of conference will be published in Scopus indexed proceedings with Springer in their prestigious “Lecture Notes in Electrical Engineering (LNEE)” series (Approval received from Springer).

We solicit original research and technical papers not published elsewhere in the following categories:

  • Full papers (10 to 12 pages in the LNEE one-column page format);

  • Short papers and poster papers (no less than 6 pages)

Conference Tracks

Original contribution for the following areas (but not limited to) are invited:

Machine Learning and Computational Intelligence

  • Theoretical Computer Science

  • Artificial Intelligence and Deep Learning

  • Pattern recognition

  • Computer Graphics

  • Virtual Reality

  • Distributed & Cloud Computing

  • Signal Processing

  • Soft Computing

  • Grid and Cluster Computing

  • Evolutionary Algorithms

  • Ubiquitous Computing

  • Parallel and Distributed Networks

  • Perceptual Computing, and related topics

  • Learning using Ensemble and boosting strategies

  • Active Machine Learning

  • Manifold Learning

  • Fuzzy Learning

  • Kernel Based Learning

  • Genetic Learning

  • Hybrid models

  • Bioinformatics and biomedical informatics

  • Healthcare and clinical decision support

  • Collaborative filtering

  • Information retrieval

  • Natural language processing

  • Web search

  • Inference dependencies on multi-layered networks

  • Recurrent Neural Networks and its applications

  • Graph wavelets

  • Spectral graph theory

  • Self-organizing networks

  • Multi-scale learning

  • Unsupervised feature learning

  • Clustering, Classification and regression methods

  • Supervised, semi-supervised and unsupervised learning

  • Reinforcement Learning

  • Optimization methods

  • Parallel and distributed learning

  • Graph embeddings

  • Genetic optimization

  • Bayesian estimation approaches

  • and related areas........

Image Processing and Computer Vision

  • Filtering, Transforms, Multi-Resolution Processing

  • Restoration, Enhancement, Super-Resolution

  • Computer Vision Algorithms and Technologies

  • Compression, Transmission, Storage, Retrieval

  • Multi-View, Stereoscopic, and 3D Processing

  • Multi-Temporal and Spatio-Temporal Processing

  • Biometrics, Forensics, and Content Protection

  • Biological and Perceptual-based Processing

  • Medical Image and Video Analysis

  • Document and Synthetic Visual Processing

  • Color and Multispectral Processing

  • Computational Imaging

  • Video Processing and Analytics

  • Visual Quality Assessment

  • Deep learning for Images and Video

  • Human activity recognition

  • Software Tools for Imaging

  • Image Generation, Acquisition, and Processing

  • Image-based Modeling and Algorithms

  • Mathematical Morphology

  • Image Geometry and Multi-view Geometry

  • 3D Imaging

  • Novel Noise Reduction Algorithms

  • Motion and Tracking Algorithms and Applications

  • Watermarking Methods and Protection

  • Wavelet Methods

  • Image Data Structures and Databases

  • Image Compression, Coding, and Encryption

  • Multi-resolution Imaging Techniques

  • Multimedia Systems and Applications

  • Novel Image Processing Applications

  • Camera Networks and Vision

  • Machine Learning Technologies for Vision

  • Cognitive and Biologically Inspired Vision

  • Active and Robot Vision

  • Fuzzy and Neural Techniques in Vision

  • Novel Document Image Understanding Techniques

  • Novel Vision Application and Case Studies

  • and related areas........


Network and Cyber Security

  • Network Performance Analysis,

  • Human factors in security and privacy

  • Security and privacy in ad hoc networks

  • Machine learning for Biometric security and privacy

  • Machine learning for Security and privacy of Web service

  • Security and privacy in e-services

  • Security and privacy in grid computing

  • Security and privacy in mobile systems

  • Security and privacy in wireless sensor networks

  • Cyber risk and vulnerability assessment

  • Cyber-crime and warfare

  • Cyber threat analysis and modelling

  • Machine learning for Bluetooth, WiFi, WiMax security

  • Security and privacy in smart grid and distributed generation systems

  • Security and privacy in social applications and networks

  • Cyber forensic tools, techniques, and analysis

  • Visual analytics for cyber security

  • Security and privacy of mobile cloud computing

  • Cyber security testbeds, tools, and methodologies

  • Active and passive cyber defense techniques

  • Insider threat detection and prevention

  • Critical infrastructure protection

  • Security and privacy in industrial systems

  • Security and privacy in pervasive/ubiquitous computing

  • Intrusion detection and prevention

  • Botnet detection and mitigation

  • and related areas........



Data Sciences and Big Data

  • Big data management,

  • Platforms and technologies for big data,

  • Data retrieval,

  • Big data storage techniques,

  • Data mining and warehouse,

  • Data visualization,

  • Modelling structure and storage of big data,

  • Scalability and portability issues of big data,

  • Big data recommender systems,

  • Digital Forensics,

  • Parallel processing of big data,

  • Distributed access of big data,

  • Applications of big data and related topics,

  • Web mining,

  • Social Network Analysis,

  • Text Mining,

  • Sentiment Analysis.

  • Algorithms

  • Novel Theoretical Models

  • Novel Computational Models

  • Data and Information Quality

  • Data Integration and Fusion

  • Cloud/Grid/Stream Computing

  • High Performance/Parallel Computing

  • Energy-efficient Computing

  • Software Systems

  • Search and Mining

  • Data Acquisition, Integration, Cleaning

  • Data Visualizations

  • Semantic-based Data Mining

  • Data Wrangling, Data Cleaning, Data Curation, Data Munching

  • Data Analysis, , Statistical Insights

  • Decision making from insights, Hidden patterns

  • Data Science technologies, tools, frameworks, platforms and APIs

  • Link and Graph Mining

  • Efficiency, scalability, security, privacy and complexity issues in Data Science

  • Labelling, Collecting, Surveying, Interviewing and other tools for Data Collection

  • Applications in Mobility, Multimedia, Science, Technology, Engineering, Medicine, Healthcare, Finance, Business, Law, Transportation, Retailing, Telecommunication

  • and related areas........