| ISBN13: | 9781032478463 |
| ISBN10: | 1032478462 |
| Binding: | Hardback |
| No. of pages: | 154 pages |
| Size: | 234x156 mm |
| Weight: | 453 g |
| Language: | English |
| Illustrations: | 53 Illustrations, black & white; 10 Halftones, black & white; 43 Line drawings, black & white; 15 Tables, black & white |
| 577 |
Engineering in general
Electrical engineering and telecommunications, precision engineering
Civil and construction engineering
Energy industry
Engineering sciences
System organization
Artificial Intelligence
Privacy, data security
Safety and health aspects of computing
Environmental sciences
Product design
Artificial Intelligence and Machine Learning
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This book focuses on Artificial Intelligence and Machine Learning technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems.
This book focuses on artificial intelligence (AI) and machine learning (ML) technologies and how they are progressively being incorporated into a wide range of products, including consumer gadgets, "smart" personal assistants, cutting-edge medical diagnostic systems, and quantum computing systems. This concise reference book offers a broad overview of the most important trends and discusses how these trends and technologies are being created and employed in the applications in which they are being used.
Artificial Intelligence and Machine Learning: An Intelligent Perspective of Emerging Technologies offers a broad package involving the incubation of AI and ML with various emerging technologies such as Internet of Things (IoT), healthcare, smart cities, robotics, and more. The book discusses various data collection and data transformation techniques and also maps the legal and ethical issues of data-driven e-healthcare systems while covering possible ways to resolve them. The book explores different techniques on how AI can be used to create better virtual reality experiences and deals with the techniques and possible ways to merge the power of AI and IoT to create smart home appliances.
With contributions from experts in the field, this reference book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.
Chapter 1. Deep Learning Strategies in Biomedicine Imaging Technique. 2. X-Ray-Based Pneumonia Detection Using ResNet50 and VGG16 Extracted Features and Conventional Machine Learning Algorithms. 3. Enrichment of Human Life through Intelligent Wearable Technology. 4. Reliability and Validity of Survey Questionnaires for Identifying Learning Disabilities in an Intelligent Tutoring System. 5. A Survey of Artificial Intelligent Techniques for Cancer Detection. 6. Ethical Issues in Medical Data. 7. AI-Based Waste Classification in the Healthcare Industry. 8. SmartWear: An IoT-Based Integration of Home Automation and Healthcare Watch. 9. An Analytical Comparison of the Identification of Non-Small Cell Lung Cancer Nodules Using CT Scans and Prominent Deep Learning Models. 10. Abnormality Classifications Using Machine Learning. 11. Multilayer Perceptron-Based Speech Emotion Recognition for Identifying the Problematic Skills of Dyslexic Learners. 12. An Improved Convolutional Neural Network-Based Detection Framework for COVID-19 Omicron and Delta Variants Employing CT Scans. 13. A Survey of IoT in Healthcare: Technologies, Applications, and Challenges.
