Understanding Artificial Intelligence: Fundamentals and Applications
- Length: 224 pages
- Edition: 1
- Language: English
- Publisher: Wiley-IEEE Press
- Publication Date: 2022-09-21
- ISBN-10: 111985833X
- ISBN-13: 9781119858331
- Sales Rank: #7150253 (See Top 100 Books)
Understanding Artificial Intelligence
Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications
Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different???many jobs will disappear, yet new jobs and opportunities will emerge.
Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text:
- Focuses on artificial intelligence applications in different industries and sectors
- Traces the history of neural networks and explains popular neural network architectures
- Covers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV)
- Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU)
- Highlights the development of new artificial intelligence hardware and architectures
Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.
Cover Table of Contents Series Page Title Page Copyright Page Dedication Page List of Figures Preface Acknowledgments Author Biographies 1 Introduction 1.1 Overview 1.2 Development History 1.3 Neural Network Model 1.4 Popular Neural Network 1.5 Neural Network Classification 1.6 Neural Network Operation 1.7 Application Development Exercise 2 Neural Network 2.1 Convolutional Layer 2.2 Activation Layer 2.3 Pooling Layer 2.4 Batch Normalization 2.5 Dropout Layer 2.6 Fully Connected Layer Exercise 3 Machine Vision 3.1 Object Recognition 3.2 Feature Matching 3.3 Facial Recognition 3.4 Gesture Recognition 3.5 Machine Vision Applications Exercise 4 Natural Language Processing 4.1 Neural Network Model 4.2 Natural Language Processing Applications Exercise 5 Autonomous Vehicle 5.1 Levels of Driving Automation 5.2 Autonomous Technology 5.3 Communication Strategies 5.4 Law Legislation 5.5 Future Challenges Exercise 6 Drone 6.1 Drone Design 6.2 Drone Structure 6.3 Drone Regulation 6.4 Applications Exercise 7 Healthcare 7.1 Telemedicine 7.2 Medical Diagnosis 7.3 Medical Imaging 7.4 Smart Medical Device 7.5 Electronic Health Record 7.6 Medical Billing 7.7 Drug Development 7.8 Clinical Trial 7.9 Medical Robotics 7.10 Elderly Care 7.11 Future Challenges Exercise 8 Finance 8.1 Fraud Prevention 8.2 Financial Forecast 8.3 Stock Trading 8.4 Banking 8.5 Accounting 8.6 Insurance Exercise 9 Retail 9.1 E‐Commerce 9.2 Virtual Shopping 9.3 Product Promotion 9.4 Store Management 9.5 Warehouse Management 9.6 Inventory Management 9.7 Supply Chain Exercise 10 Manufacturing 10.1 Defect Detection 10.2 Quality Assurance 10.3 Production Integration 10.4 Generative Design 10.5 Predictive Maintenance 10.6 Environment Sustainability 10.7 Manufacturing Optimization Exercise 11 Agriculture 11.1 Crop and Soil Monitoring 11.2 Agricultural Robot 11.3 Pest Control 11.4 Precision Farming Exercise 12 Smart City 12.1 Smart Transportation 12.2 Smart Parking 12.3 Waste Management 12.4 Smart Grid 12.5 Environmental Conservation Exercise 13 Government 13.1 Information Technology 13.2 Human Service 13.3 Law Enforcement 13.4 Homeland Security 13.5 Legislation 13.6 Ethics 13.7 Public Perspective Exercise 14 Computing Platform 14.1 Central Processing Unit 14.2 Graphics Processing Unit 14.3 Tensor Processing Unit 14.4 Neural Processing Unit Exercise Appendix A: Kneron Neural Processing Unit Appendix B: Object Detection – Overview B.1 Kneron Environment Setup B.2 Python Installation B.3 Library Installation B.4 Driver Installation B.5 Model Installation B.6 Image/Camera Detection B.7 Yolo Class List Appendix C: Object Detection – Hardware C.1 Library Setup C.2 System Parameters C.3 NPU Initialization C.4 Image Detection C.5 Camera Detection Appendix D: Hardware Transfer Mode D.1 Serial Transfer Mode D.2 Pipeline Transfer Mode D.3 Parallel Transfer Mode Appendix E: Object Detection – Software (Optional) E.1 Library Setup E.2 Image Detection E.3 Video Detection References Index End User License Agreement
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