Читать книгу Machine Learning Paradigm for Internet of Things Applications - Группа авторов - Страница 2
Table of Contents
Оглавление1 Cover
4 Preface
5 1 Machine Learning Concept–Based IoT Platforms for Smart Cities’ Implementation and Requirements 1.1 Introduction 1.2 Smart City Structure in India 1.3 Status of Smart Cities in India 1.4 Analysis of Smart City Setup 1.5 Ideal Planning for the Sewage Networking Systems 1.6 Heritage of Culture Based on Modern Advancement 1.7 Funding and Business Models to Leverage 1.8 Community-Based Development 1.9 Revolutionary Impact With Other Locations 1.10 Finding Balanced City Development 1.11 E-Industry With Enhanced Resources 1.12 Strategy for Development of Smart Cities References
6 2 An Empirical Study on Paddy Harvest and Rice Demand Prediction for an Optimal Distribution Plan 2.1 Introduction 2.2 Background 2.3 Methodology 2.4 Results and Discussion 2.5 Conclusion References
7 3 A Collaborative Data Publishing Model with Privacy Preservation Using Group-Based Classification and Anonymity 3.1 Introduction 3.2 Literature Survey 3.3 Proposed Model 3.4 Results 3.5 Conclusion References
8 4 Production Monitoring and Dashboard Design for Industry 4.0 Using Single-Board Computer (SBC) 4.1 Introduction 4.2 Related Works 4.3 Industry 4.0 Production and Dashboard Design 4.4 Results and Discussion 4.5 Conclusion References
9 5 Generation of Two-Dimensional Text-Based CAPTCHA Using Graphical Operation 5.1 Introduction 5.2 Types of CAPTCHAs 5.3 Related Work 5.4 Proposed Technique 5.5 Text-Based CAPTCHA Scheme 5.6 Breaking Text-Based CAPTCHA’s Scheme 5.7 Implementation of Text-Based CAPTCHA Using Graphical Operation 5.8 Graphical Text-Based CAPTCHA in Online Application 5.9 Conclusion and Future Enhancement References
10 6 Smart IoT-Enabled Traffic Sign Recognition With High Accuracy (TSR-HA) Using Deep Learning 6.1 Introduction 6.2 Experimental Evaluation 6.3 Conclusion References
11 7 Offline and Online Performance Evaluation Metrics of Recommender System: A Bird’s Eye View 7.1 Introduction 7.2 Evaluation Metrics 7.3 Related Works 7.4 Experimental Setup 7.5 Summary and Conclusions References
12 8 Deep Learning–Enabled Smart Safety Precautions and Measures in Public Gathering Places for COVID-19 Using IoT 8.1 Introduction 8.2 Prelims 8.3 Proposed System 8.4 Math Model 8.5 Results 8.6 Conclusion References
13 9 Route Optimization for Perishable Goods Transportation System 9.1 Introduction 9.2 Related Works 9.3 Proposed Methodology 9.4 Proposed Work Implementation 9.5 Conclusion References
14 10 Fake News Detection Using Machine Learning Algorithms 10.1 Introduction 10.2 Literature Survey 10.3 Methodology 10.4 Experimental Results 10.5 Conclusion References
15 11 Opportunities and Challenges in Machine Learning With IoT 11.1 Introduction 11.2 Literature Review 11.3 Why Should We Care About Learning Representations? 11.4 Big Data 11.5 Data Processing Opportunities and Challenges 11.6 Learning Opportunities and Challenges 11.7 Enabling Machine Learning With IoT 11.8 Conclusion References
16 12 Machine Learning Effects on Underwater Applications and IoUT 12.1 Introduction 12.2 Characteristics of IoUT 12.3 Architecture of IoUT 12.4 Challenges in IoUT 12.5 Applications of IoUT 12.6 Machine Learning 12.7 Simulation and Analysis 12.8 Conclusion References
17 13 Internet of Underwater Things: Challenges, Routing Protocols, and ML Algorithms 13.1 Introduction 13.2 Internet of Underwater Things 13.3 Routing Protocols of IoUT 13.4 Machine Learning in IoUT 13.5 Performance Evaluation 13.6 Conclusion References
18 14 Chest X-Ray for Pneumonia Detection 14.1 Introduction 14.2 Background 14.3 Research Methodology 14.4 Results and Discussion 14.5 Conclusion Acknowledgment References
19 Index
