Description
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems.
The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications.
Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems.
Features
- Includes AI-based decision-making approaches
- Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images
- Covers automation of systems through machine learning and deep learning approaches and its implications to the real world
- Presents data analytics and mining for decision-support applications
- Offers case-based reasoning
Table of Contents
1. An Artificial Intelligence System Based Power Estimation Method for CMOS VLSI Circuits
[Govindaraj Vellingiri and Ramesh Jayabalan]
2. Awareness Alert and Information Analysis in Social Media Networking Using Usage Analysis and Negotiable Approach
[Alamelu Muthukrishnan]
3. Object Detection and Tracking in Video Using Deep Learning Techniques: A Review
[Dhivya Praba Ramasamy and Kavitha Kanagaraj]
4. Fuzzy MCDM: Application in Disease Risk and Prediction
[Rachna Jain, Meenu Gupta, Abhishek Kathuria, and Devanshi Mukhopadhyay]
5. Deep Learning Approach to Predict and Grade Glaucoma from Fundus Images through Constitutional Neural Networks
[Kishore Balasubramanian and N. B. Ananthamoorthy]
6. A Novel Method for Securing Cognitive Radio Communication Network Using the Machine Learning Schemes and a Rule Based Approaches
[Antony Hyils Sharon Magdalene and Lakshmanan Thulasimani]
7. Detection of Retinopathy of Prematurity Using Convolution Neural Network
[Deepa Dhanaskodi and Poongodi Chenniappan]
8. Impact of Technology on Human Resource Information System and Achieving Business Intelligence in Organizations
[Sharanika Dhal, Manas Kumar Pal, Archana Choudhary, and Mamata Rath]
9. Proficient Prediction of Acute Lymphoblastic Leukemia Using Machine Learning Algorithm
[M. Sangeetha, K.N. Apinaya Prethi, and S. Nithya]
10. Role of Machine Learning in Social Area Networks
[Rajeswari Arumugam, Premalatha Balasubramaniam, and Cynthia Joseph]
11. Breast Cancer and Machine Learning: Interactive Breast Cancer Prediction Using Naïve Bayes Algorithm
[Atapaka Thrilok Gayathri and Samuel Theodore Deepa]
12. Deep Networks and Deep Learning Algorithms
[Tannu Kumari and Anjana Mishra]
13. Machine Learning for Big Data Analytics, Interactive and Reinforcement
[Ritwik Raj and Anjana Mishra]
14. Fish Farm Monitoring System Using IoT and Machine Learning
[Farjana Yeasmin Trisha, Mohammad Farhan Ferdous, and Mahmudul Hasan]
