Machine Learning Applications : From Computer Vision to Robotics

✍ Scribed by Chatterjee, Indranath; Zalte, Sheetal; Sheetal Zalte

• Publisher: Wiley
• Year: 2023
• Tongue: English
• Leaves: 240
• Category: Library

✦ Synopsis

Machine Learning Applications

Practical resource on the importance of Machine Learning and Deep Learning applications in various technologies and real-world situations

Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and delivers real-world applications in healthcare to identify diseases and diagnosis, such as creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader’s active learning.

Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The book describes the importance of each subject area and detail why they are so important to us from a societal and human perspective.

Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, Machine Learning Applications includes information on

Content based medical image retrieval (CBMIR), covering face and vehicle detection, multi-resolution and multisource analysis, manifold and image processing, and morphological processing
Smart medicine, including machine learning and artificial intelligence in medicine, risk identification, tailored interventions, and association rules
AI and robotics application for transportation and infrastructure (e.g., autonomous cars and smart cities), along with global warming and climate change
Identifying diseases and diagnosis, drug discovery and manufacturing, medical imaging diagnosis, personalized medicine, and smart health records

With its practical approach to the subject, Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.

✦ Table of Contents

Cover
Table of Contents
Series Page
Title Page
Copyright Page
About the Authors
Preface
1 Statistical Similarity in Machine Learning
1.1 Introduction
1.2 Featureless Machine Learning
1.3 Two‐Sample Homogeneity Measure
1.4 The Klyushin–Petunin Test
1.5 Experiments and Applications
1.6 Summary
References
2 Development of ML‐Based Methodologies for Adaptive Intelligent E‐Learning Systems and Time Series Analysis Techniques
2.1 Introduction
2.2 Methodological Advancement of Machine Learning
2.3 Machine Learning on Time Series Analysis
2.4 Conclusion
Acknowledgment
Conflict of Interest
References
3 Time‐Series Forecasting for Stock Market Using Convolutional Neural Network
3.1 Introduction
3.2 Materials
3.3 Methodology
3.4 Accuracy Measurement
3.5 Result and Discussion
3.6 Conclusion
Acknowledgement
References
4 Comparative Study for Applicability of Color Histograms for CBIR Used for Crop Leaf Disease Detection
4.1 Introduction
4.2 Literature Review
4.3 Methodology
4.4 Results and Discussions
4.5 Conclusion
References
Biographies of Authors
5 Stock Index Forecasting Using RNN‐Long Short‐Term Memory
5.1 Introduction
5.2 Materials
5.3 Methodology
5.4 Result and Discussion
5.5 Conclusion
Acknowledgement
References
6 Study and Analysis of Machine Learning Models for Detection of Phishing URLs
6.1 Introduction
6.2 Literature Review
6.3 Methodology
6.4 Results and Experimentation
6.5 Model‐Metric Analysis
6.6 Conclusion
References
7 Real‐World Applications of BC Technology in Internet of Things
7.1 Introduction
7.2 Review of Existing Study
7.3 Background of Blockchain
7.4 Blockchain Technology in Internet of Things
7.5 Challenges and Concerns in Integrating Blockchain with the IoT
7.6 Blockchain Applications for the Internet of Things (BIoT Applications)
7.7 Application of BIoT in Healthcare
7.8 Application of BIoT in Voting
7.9 Application of BIoT in Supply Chain
7.10 Summary
References
8 Advanced Persistent Threat
8.1 Introduction
8.2 Background Study
8.3 Literature Review
8.4 Research Questions
8.5 Research Objectives
8.6 Research Hypothesis
8.7 Phases of APT Outbreak
8.8 Research Methodology
8.9 A Deception Exemplary of Counter‐Offensive
8.10 Conclusion
Acknowledgment
Conflict of Interest
References
9 Integration of Blockchain Technology and Internet of Things: Challenges and Solutions
9.1 Introduction
9.2 Overview of Blockchain–IoT Integration
9.3 How Blockchain–IoT Work Together
9.4 Blockchain–IoT Applications
9.5 Related Studies on Integration of IoT and Blockchain Applications
9.6 Challenges of Blockchain–IoT Integration
9.7 Solutions of Blockchain‐IoT Integration
9.8 Future Directions for Blockchain–IoT Integration
9.9 Conclusion
References
10 Machine Learning Techniques for SWOT Analysis of Online Education System
10.1 Introduction
10.2 Motivation
10.3 Objectives
10.4 Methodology
10.5 Dataset Preparation
10.6 Data Visualization and Analysis
10.7 Machine Learning Techniques Implementation
10.8 Conclusion
References
11 Crop Yield and Soil Moisture Prediction Using Machine Learning Algorithms
11.1 Introduction
11.2 Literature Review
11.3 Methodology
11.4 Result and Discussion
11.5 Conclusion
References
12 Multirate Signal Processing in WSN for Channel Capacity and Energy Efficiency Using Machine Learning
12.1 Introduction
12.2 Energy Management in WSN
12.3 Different Strategies to Increase Energy Efficiency
12.4 Algorithm Development
12.5 Results
12.6 Summary
References
13 Introduction to Mechanical Design of AI‐Based Robotic System
13.1 Introduction
13.2 Mechanisms in a Robot
13.3 Kinematics
13.4 Conclusion
Acknowledgment
Conflict of Interest
References
Index
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