Special Sessions

SS1/ Special Session on: "Computer Vision and Multimedia Forensic"

Computer Vision and Multimedia Forensic covering all aspects of video, image analysis from the low-level, iconic processes of early vision to the high-level, symbolic processes of recognition and interpretation. A wide range of topics in the image understanding area is also covered. The main objective of this special session is to showcasing the latest advances and trends in computer vision and machine learning algorithms for image and video security. Its scope is interdisciplinary and seeks collaborative contributions from academia and industrial experts in the areas of image processing, signal processing, computer vision, machine learning and data science.

Manuscripts are solicited to address a wide range of all topics on computer vision techniques but not limited to the following:

    • Performance Evaluation and Benchmark Datasets
    • Multi-sensor Data Analysis, 3D Computer Vision
    • Big Data, Large Scale Methods
    • Object/ Target Detection, Recognition and Identification
    • Machine Learning for Computer Vision
    • Deep Learning for Computer Vision
    • Image forensic
    • Copy-move forgery detection
    • Audio, Image and video watermarking
    • Image Tampering Detection
    • Video Tampering Detection
    • Biometric image processing and recognition
    • Fingerprint identification and recognition
    • Face Detection and recognition


Chairman of Special Session: Dr. Pradip K Das, Professor, Indian Institute of Technology Guwahati

Special Session Convenor: Dr. Badal Soni, Assistant Professor, National Institute of Technology Silchar

Special Session Co-Convenor : Dr. Partha Pakray, Assistant Professor, National Institute of Technology Silchar

Email ID: soni.badal88@gmail.com, parthapakray@gmail.com

SS2/ Special Session on: "Advances in Deep Learning Algorithms for Information Security"

In the age of Internet computer networks play a pivotal role in it’s growth and development. Client server, P2P, VPN, CDNs communication and services provide backbone to this framework. It is under this scenario that Information Security in general and Computer Network Security in particular has significant role to play. Humongous success of the Internet based services has made both the user and the machine vulnerable to damaging exploits. Now-a-days one has to deal with security of personal computers, laptops, servers, mobile devices, smart devices etc. The field of Information security is vast covering topics ranging from Viruses, worms, phishing attacks, Trojans, malwares, spam detection, botnets, forensics, cryptography, web security, firewalls, intrusion detection, anomaly detection and much more. Various techniques and algorithms have been developed to provide fast and accurate security solutions. Traditional statistical intrusion detection techniques are no longer suitable enough to handle big data streams of the network traffic and there is need for new algorithms to be looked into like deep learning, fuzzy, evolutionary algorithms, etc. Random Forest, AdaBoost, SVM, k-means, k-medoids, clustering, hierarchical clustering, fuzzy c-means clustering, intuitionistic fuzzy, neural learning are some of the algorithms being worked on in this field.

In this session original scientific and technical papers are invited for following topics, but not limited to:

    • Deep learning architectures
    • Deep learning in DDoS, LDoS, PDoS Detection
    • Deep learning in Botnet Detection
    • Deep learning in Phishing and Spam Detection
    • Deep NLP for Network Anomaly Detection
    • Deep learning for Malware identification, analysis and similarity
    • Deep learning for biasness in Social Networks
    • Deep learning for Web Security
    • Deep learning for Computer Forensics• Deep learning for VPN Security
    • Deep learning for CDN Security
    • Deep learning for data security in mobile devices
    • Deep learning for security in big data networks
    • Deep learning for cloud security
    • Deep learning for SDN and FoG networks


Dr. Gagandeep Kaur, Ph.D

Faculty of Computer Science Engineering & Information Technology

Jaypee Institute of Information Technology, India

E-mail: gagandeep.kaur@jiit.ac.in, dr.gagandeepkaur15@gmail.com

SS3/ Special Session on: "Artificial Intelligence: Applications in Software Engineering"

Software engineering (SE) field is evolving fast to meet the requirements of modern-day software systems and to cope with the challenges imposed by the unstoppable technological innovations. As Artificial Intelligence (AI) techniques are becoming more powerful and easier to apply, they can be deployed to improve the software development process and practices. AI areas such as Semantic Web and Knowledge Engineering play a crucial role in shaping the modern web and software-as-a-service. Further, Machine learning is omnipresent across software quality assessment, fault prediction, and for examining a large amount of data to uncover useful information pertinent to software. There are abundant opportunities available to apply the hybridization of AI/Machine Learning and SE. Deep learning is a sub-field of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Therefore, there is an urgent need to explore the applications of AI techniques for SE problems.

Original technical papers as contributions are solicited to address a broad scope of AI applications in software engineering, however, not limited to the following:

  • Applications of ontologies in software development life cycle
  • AI paradigm in removing software bugs
  • Mobile software’s malware analysis with deep learning
  • Semantic web applications’ quality assessment
  • Machine learning to predict Software As a Service (SaaS) quality
  • Software fault prediction using machine learning and AI techniques
  • Applications of Search based Techniques in software engineering
  • Knowledge engineering for modular development of software
  • Information retrieval from health and social media domain using semantic web
  • Software clones and their detection through AI
  • Knowledge based software systems
  • Fuzzy rule based software for decision making


Dr. Niyati Baliyan

Assistant Professor

Department of Information Technology

Indira Gandhi Delhi Technical University for Women (IGDTUW), New Delhi

Email: niyatibaliyan@igdtuw.ac.in

Dr. Santosh Singh Rathore

Assistant Professor

Department of Computer Science and Engineering,

National Institute of Technology Jalandhar, India

Email: rathores@nitj.ac.in

Any query related to special sessions must be addressed to info@mind2019.in