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Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

Latest Trends in AI, Volume 2

  • Book
  • © 2021

Overview

Editors:
  1. Vinit Kumar Gunjan

    1. Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, India

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    You can also search for this editor in PubMed   Google Scholar

  2. Jacek M. Zurada

    1. Department of Electrical and Computer Engineering, University of Louisville, Louisville, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Presents recent trends and approaches highlighting the multidisciplinarity of machine learning and cognitive science
  • Provides a valuable reference resource for students, researchers, and industry practitioners
  • Combines machine learning and cognitive science, and other aspects of AI

Part of the book series: Studies in Computational Intelligence (SCI, volume 956)

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About this book

This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development.

The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming.

Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains. 

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Table of contents (40 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Using CNN to Predict Regressive STD Drug Efficacy Score

    • Ambarish Moharil, Mansimran Singh Anand, Chirag Kedia, Nikhil Sonavane
    Pages 1-12

  3. Emotion Recognition in Hindi Speech Using CNN-LSTM Model

    • B. Shashank, Bhavani Shankar, L. Chandresh, R. Jayashree
    Pages 13-22

  4. Refinery Profit Planning via Evolutionary Many-Objective Optimization

    • Vadlamani Madhav, Shaik Tanveer-Ul Huq, Vadlamani Ravi
    Pages 23-31

  5. A Deep Learning Technique for Image Inpainting with GANs

    • K. A. Suraj, Sumukh H. Swamy, Shrijan S. Shetty, R. Jayashree
    Pages 33-42

  6. A Comparative Study on Distributed File Systems

    • Suman De, Megha Panjwani
    Pages 43-51

  7. An Organized Approach for Analysis of Diabetic Nephropathy Images Using Watershed and Contrast Adaptive Thresholding

    • Syed Musthak Ahmed, Fahimuddin Shaik, Vinit Kumar Gunjan, Mohammed Yasin Ali
    Pages 53-67

  8. A Literature Survey on Identification of Asthma Using Different Classifier and Clustering Techniques

    • Syed Musthak Ahmed, Fahimuddin Shaik, Vinit Kumar Gunjan, Mohammed Yasin Ali
    Pages 69-80

  9. Adaptation and Evolution of Decision Support Systems—A Typological Survey

    • Ravi Lourdusamy, Xavierlal J. Mattam
    Pages 81-94

  10. Real-Time Implementation of Brain Emotional Controller for Sensorless Induction Motor Drive with Adaptive System

    • Sridhar Savarapu, Yadaiah Narri
    Pages 95-113

  11. Student Performance Prediction—A Data Science Approach

    • Y. Sri Lalitha, Y. Gayathri, M. V. Aditya Nag, Sk. Althaf Hussain Basha
    Pages 115-125

  12. HARfog: An Ensemble Deep Learning Model for Activity Recognition Leveraging IoT and Fog Architectures

    • R. Raja Subramanian, V. Vasudevan
    Pages 127-136

  13. Performance Evaluation and Identification of Optimal Classifier for Credit Card Fraudulent Detection

    • Arpit Bhushan Sharma, Brijesh Singh
    Pages 137-155

  14. Potential Use-Cases of Natural Language Processing for a Logistics Organization

    • Rachit Garg, Arvind W. Kiwelekar, Laxman D. Netak, Swapnil S. Bhate
    Pages 157-191

  15. Partial Consensus and Incremental Learning Based Intrusion Detection System

    • Mohd Mohtashim Nawaz, Vineet Gupta, Jagrati Rawat, Kumar Prateek, Soumyadev Maity
    Pages 193-201

  16. AI Enabled Context Sensitive Information Retrieval System

    • Binil Kuriachan, Gopikrishna Yadam, Lakshmi Dinesh
    Pages 203-214

  17. Personalization of News for a Logistics Organisation by Finding Relevancy Using NLP

    • Rachit Garg, Arvind W Kiwelekar, Laxman D Netak, Swapnil S Bhate
    Pages 215-226

  18. AI Model Compression for Edge Devices Using Optimization Techniques

    • Uday Kulkarni, S. M. Meena, Sunil V. Gurlahosur, Pratiksha Benagi, Atul Kashyap, Ayub Ansari et al.
    Pages 227-240

  19. An Empirical Study and Analysis of Various Electroencephalography (EEG) Artefact Removal Methods

    • J. Vishwesh, P. Raviraj
    Pages 241-253

  20. Chatbot via Machine Learning and Deep Learning Hybrid

    • Basit Ali, Vadlamani Ravi, Chandra Bhushan, M. G. Santhosh, O. Shiva Shankar
    Pages 255-265
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Editors and Affiliations

  • Department of Computer Science and Engineering, CMR Institute of Technology, Hyderabad, India

    Vinit Kumar Gunjan

  • Department of Electrical and Computer Engineering, University of Louisville, Louisville, USA

    Jacek M. Zurada

Bibliographic Information

  • Book Title: Modern Approaches in Machine Learning and Cognitive Science: A Walkthrough

  • Book Subtitle: Latest Trends in AI, Volume 2

  • Editors: Vinit Kumar Gunjan, Jacek M. Zurada

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-68291-0

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-68290-3Published: 27 April 2021

  • Softcover ISBN: 978-3-030-68293-4Published: 28 April 2022

  • eBook ISBN: 978-3-030-68291-0Published: 26 April 2021

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: X, 515

  • Number of Illustrations: 80 b/w illustrations, 154 illustrations in colour

  • Topics: Computational Intelligence, Machine Learning

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