1st Edition
Machine Learning Hybridization and Optimization for Intelligent Applications
This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation.
Features:
• Focuses on hybridization and optimization of machine learning techniques.
• Reviews supervised, unsupervised, and reinforcement learning using case study-based applications.
• Covers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computing.
• Explains computing models using real-world examples and dataset-based experiments.
• Includes case study-based explanations and usage for machine learning technologies and applications.
This book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
1. Big Data Computing: Transforming From Cloud Computing to Edge Scheduling Perspectives Review
Sandhya Rani Nallola and Vadivel Ayyasamy
2. Decision Making in the Field of Unmanned Aerial Vehicles: State-of-the-Art
Sohini Ghosh, Bishwayan Ghosh, Suneeta Mohanty, and Prasant Kumar Pattnaik
3. A Brief Study on Understanding and Handling COVID-19: Test Bed for Forecasting with Deep Learning and Machine Learning Algorithms
M. Premalatha, G. Anusooya, G. Suganya, M. Braveen, and Venkatasubramanian Adhinarayanan
4. AgTech: Using Sensors and Machine Learning to Revolutionize Farming Practices (IoT)
Shola Usharani, Alabhya Sharma, Aniket Kulkarni, Abhay Arora, and Hritik Goel
5. Developing an AI-based Multi-Task Transfer Learning Framework for Automating Judicial Contracts
R V Aswiga
6. Analysis of Deep Learning Methodologies for Handling Non-Medical Big Data and Very Limited Medical Data with Feature Extraction and Annotation Techniques
R V Aswiga
7. Introduction to Virtualization Security and Cloud Security
Sonal Sharma, D.Lohith Kumar, and Er. Ashish Vijay
8.Security Breaches in IoT Applications: An Extensive Study
C Silpa, Niranjana Govindan, and K Ramani
9. An Efficient and Accurate Classifcation Algorithm for ECG Signals Using PNN and KNN
R. Anandha Praba, L. Suganthi, and E.S. Selva Priya
10. Big Data Analytics: The Classification of Remote Sensing Images Using Machine Learning Techniques
V Pushpalatha, H N Mahendra, Shoaib Kamal, and S Mallikarjunaswamy
11. Segmentation of Transmission Tower Components Based on Machine Learning
Satheeswari Damodaran, Leninisha Shanmugam, K Parkavi, Nirmala Venkatachalam, and N.M. Jothi Swaroopan
12. A Systematic Analysis of Robot Path Planning and Optimization Techniques
Pallapothala Tejaswini, Kaushlendra Sharma, and Rajesh Doriya
13. Pneumonia Prediction Model Using Deep Learning on Docker
Yash Seth, Philip Anand, Jinen Rathore, R Gayathri, and Shola Usharani
14. A Sequential Deep Learning Model Approach to OCR-Based Handwritten Digit Recognition for Physically Impaired People
S Charan, Sheena Christabel Pravin, G Rohith, V Kiruthika, And T Yaswant
15. A Deep Learning Strategy for Sign Language Classification and Recognition for Hearing-Impaired People
Souvagya Ganguli, Sumit Anand, Supriti Das, and G Rohith
16. Non-fungible Tokens (NFT): The Design and Development of the "Obstacle Assault" Game and "Turtle Sidestep" Game
Sam Methuselah, Vishal Singh, Neel Raval, Vedant Bisen, Adrika Tamuly, Sisira Mondreti, Prince Attri, and G Rohith
17. Design and Development of 2D Space Shooter Game and Arcade Game Using Unity
Jaiveer Singh Rathore, Arunava Mukherjee, N Sradha, Saumya Bhardwaj, Rohan Purkait, Harsh Mathur, and G Rohith
18. An Ensemble Technique Using Genetic Algorithm and Deep Learning for the Prediction of Rice Diseases
Sunanda Das, Tanvir H. Sardar, and DS Sahana
19. History of Machine Learning
Deepak K. Sinha and Garima Sinha
20. Internet of Things Start-Ups: An Overview of the Privacy and Security in IoT Start-Ups
M Suguna, Aswathy Sreenivasan, M Suresh, and C U Om Kumar
Biography
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.
