Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithm

  • 5h 33m
  • Rohit Raja, Sandeep Kumar, Shilpa Rani, Shrikant Tiwari
  • John Wiley & Sons (US)
  • 2021


The objective of this book is to provide the most relevant information on Human-Computer Interaction to academics, researchers, and students and for those from industry who wish to know more about the real-time application of user interface design.

Human-computer interaction (HCI) is the academic discipline, which most of us think of as UI design, that focuses on how human beings and computers interact at ever-increasing levels of both complexity and simplicity. Because of the importance of the subject, this book aims to provide more relevant information that will be useful to students, academics, and researchers in the industry who wish to know more about its real-time application. In addition to providing content on theory, cognition, design, evaluation, and user diversity, this book also explains the underlying causes of the cognitive, social and organizational problems typically devoted to descriptions of rehabilitation methods for specific cognitive processes. Also described are the new modeling algorithms accessible to cognitive scientists from a variety of different areas.

This book is inherently interdisciplinary and contains original research in computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Since machine learning research has already been carried out for a decade in various applications, the new learning approach is mainly used in machine learning-based cognitive applications. Since this will direct the future research of scientists and researchers working in neuroscience, neuroimaging, machine learning-based brain mapping, and modeling, etc., this book highlights the framework of a novel robust method for advanced cross-industry HCI technologies. These implementation strategies and future research directions will meet the design and application requirements of several modern and real-time applications for a long time to come.

Audience: A wide range of researchers, industry practitioners, and students will be interested in this book including those in artificial intelligence, machine learning, cognition, computer programming and engineering, as well as social sciences such as psychology and linguistics.

About the Author

Sandeep Kumar, PhD is a Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India. He has published more than 100 research papers in various international/national journals and 6 patents. He has been awarded the “Best Excellence Award” in New Delhi, 2019.

Rohit Raja, PhD is an associate professor in the IT Department at the Guru Ghasidas, Vishwavidyalaya, Bilaspur (Central University-CG). He gained his PhD in Computer Science and Engineering in 2016 from C. V. Raman University India. He has filed successfully 10 (9 national + 1 international) patents and published more than 80 research papers in various international/national journals.

Shrikant Tiwari, PhD is an assistant professor in the Department of Computer Science & Engineering (CSE) at Shri Shankaracharya Technical Campus, Junwani, Bhilai, Distt. Chattisgarh, India. He received his PhD from the Department of Computer Science & Engineering (CSE) from the Indian Institute of Technology (Banaras Hindu University), Varanasi (India) in 2012.

Shilpa Rani, PhD is an assistant professor in the Department of Computer Science & Engineering, Neil Gogte Institute of Technology, Hyderabad, India.

In this Book

  • Cognitive Behavior—Different Human-Computer Interaction Types
  • Classification of HCI and Issues and Challenges in Smart Home HCI Implementation
  • Teaching-Learning Process and Brain-Computer Interaction Using ICT Tools
  • Denoising of Digital Images Using Wavelet-Based Thresholding Techniques—A Comparison
  • Smart Virtual Reality–Based Gaze-Perceptive Common Communication System for Children with Autism Spectrum Disorder
  • Construction and Reconstruction of 3D Facial and Wireframe Model Using Syntactic Pattern Recognition
  • Attack Detection Using Deep Learning-Based Multimodal Biometric Authentication System
  • Feature Optimized Machine Learning Framework for Unbalanced Bioassays
  • Predictive Model and Theory of Interaction
  • Advancement in Augmented and Virtual Reality
  • Computer Vision and Image Processing for Precision Agriculture
  • A Novel Approach for Low-Quality Fingerprint Image Enhancement Using Spatial and Frequency Domain Filtering Techniques
  • Elevate Primary Tumor Detection Using Machine Learning
  • Comparative Sentiment Analysis Through Traditional and Machine Learning-Based Approach
  • Application of Artificial Intelligence and Computer Vision to Identify Edible Bird’s Nest
  • Enhancement of Satellite and Underwater Image Utilizing Luminance Model by Color Correction Method