Machine Learning Hybridization and Optimization for Intelligent Applications (eBook, PDF)

Redaktion: Sardar, Tanvir Habib; Pandey, Bishwajeet Kumar

• Format: PDF

Produktbeschreibung

This book discusses state-of-the-art reviews of the existing machine-learning techniques and algorithms including hybridizations and optimizations. It is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 366
• Erscheinungstermin: 28. Oktober 2024
• Englisch
• ISBN-13: 9781040130353
• Artikelnr.: 72280407

Autorenporträt

Tanvir Habib Sardar is an Assistant Professor in the department of CSE at GITAM University, Bengaluru campus. He has more than fifteen years of experience in industry and academia. His research domain is big data, machine learning, fuzzy logic, and distributed computing using MapReduce. Bishwajeet Kumar Pandey is a Professor at Department of Intelligent System and Cyber Security, Astana IT University Kazaksthan. He is also a visiting professor at Eurasian National University, Astana, Kazaksthan (QS World Rank 355) and UCSI University, Kuala Lumpur, Malaysia (QS World Rank 300). He has interest in Green Computing, High-Performance Computing, Cyber-Physical Systems, Machine Learning, and Cyber Security.

Inhaltsangabe

1. Big Data Computing: Transforming From Cloud Computing to Edge Scheduling
Perspectives Review. 2. Decision Making in the Field of Unmanned Aerial
Vehicles: State-of-the-Art. 3. A Brief Study on Understanding and Handling
COVID-19: Test Bed for Forecasting with Deep Learning and Machine Learning
Algorithms. 4. AgTech: Using Sensors and Machine Learning to Revolutionize
Farming Practices (IoT). 5. Developing an AI-based Multi-Task Transfer
Learning Framework for Automating Judicial Contracts. 6. Analysis of Deep
Learning Methodologies for Handling Non-Medical Big Data and Very Limited
Medical Data with Feature Extraction and Annotation Techniques. 7.
Introduction to Virtualization Security and Cloud Security. 8.Security
Breaches in IoT Applications: An Extensive Study. 9.An Efficient and
Accurate Classifcation Algorithm for ECG Signals Using PNN and KNN. 10. Big
Data Analytics: The Classification of Remote Sensing Images Using Machine
Learning Techniques. 11. Segmentation of Transmission Tower Components
Based on Machine Learning. 12. A Systematic Analysis of Robot Path Planning
and Optimization Techniques. 13.Pneumonia Prediction Model Using Deep
Learning on Docker. 14. A Sequential Deep Learning Model Approach to
OCR-Based Handwritten Digit Recognition for Physically Impaired People. 15.
A Deep Learning Strategy for Sign Language Classification and Recognition
for Hearing-Impaired People. 16. Non-fungible Tokens (NFT): The Design and
Development of the "Obstacle Assault" Game and "Turtle Sidestep" Game. 17.
Design and Development of 2D Space Shooter Game and Arcade Game Using
Unity. 18. An Ensemble Technique Using Genetic Algorithm and Deep Learning
for the Prediction of Rice Diseases. 19. History of Machine Learning. 20.
Internet of Things Start-Ups: An Overview of the Privacy and Security in
IoT Start-Ups.