Neural Networks, Machine Learning, and Image Processing
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Neural Networks, Machine Learning, and Image Processing: Mathematical Modeling and Applications

Neural Networks, Machine Learning, and Image Processing: Mathematical Modeling and Applications

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About the Book

The text comprehensively discusses the latest mathematical modelling techniques and their applications in various areas such as fuzzy modelling, signal processing, neural network, machine learning, image processing, and their numerical analysis. It further covers image processing techniques like Viola-Jones Method for face detection and fuzzy approach for person video emotion. It will serve as an ideal reference text for graduate students and academic researchers in the fields of mechanical engineering, electronics, communication engineering, computer engineering, and mathematics. This book: Discusses applications of neural networks, machine learning, image processing, and mathematical modeling. Provides simulations techniques in machine learning and image processing-based problems. Highlights artificial intelligence and machine learning techniques in the detection of diseases. Introduces mathematical modeling techniques such as wavelet transform, modeling using differential equations, and numerical techniques for multi-dimensional data. Includes real-life problems for better understanding. The book presents mathematical modeling techniques such as wavelet transform, differential equations, and numerical techniques for multi-dimensional data. It will serve as an ideal reference text for graduate students and academic researchers in diverse engineering fields such as mechanical, electronics and communication and computer.

Table of Contents:
Chapter 1 Mathematical Modeling on Thermoregulation in Sarcopenia 1.1. Introduction 1.2. Discretization 1.3. Modeling and Simulation of Basal Metabolic Rate and Skin Layers Thickness 1.4. Mathematical Model and Boundary Conditions 1.5. Solution of the Model 1.6. Numerical Results and discussion 1.7. Conclusion References Chapter 2 Multi-objective University Course Scheduling for Uncertainly Generated Courses 2.1 Introduction 2.2 Literature review 2.3 Formulation of problem 2.4 Methodology 2.5 Numerical Example 2.6 Result and Discussion 2.7 Conclusion References Chapter 3 MChCNN : A Deep Learning Approach to Detect Text based Hate Speech 3.1. Introduction Background and Driving Forces 3.2. Related Work 3.3. Experiment and Results 3.4. Conclusion References Chapter 4 PSO Based PFC Cuk Converter fed BLDC Motor Drive for Automotive Applications 4.1. Introduction 4.2. Operation of Cuk converter fed BLDC motor drive system 4.3. Controller Operation 4.4. Result and Discussion 4.5. Conclusion References Chapter 5 Optimize Feature Selection for Condition based monitoring of Cylindrical bearing using Wavelet transform and ANN 5.1. Introduction 5.2. Methodology 5.3. Data Preparation 5.4. Result and Discussion 5.5. Conclusion References Chapter 6 SafeShop - An integrated system for safe pickup of items during COVID-19 6.1. Introduction 6.2. Literature Survey 6.3. Methodology 6.4. Result and Discussion 6.5. Conclusion References Chapter 7 Solution of First Order Fuzzy Differential Equation using Numerical Method 7.1. Introduction 7.2. Preliminaries 7.3. Methodology 7.4. Illustration 7.5. Conclusion References SECTION II Simulations in Machine Learning and Image Processing Chapter 8 Multi-layer Encryption Algorithm for Data Integrity in Cloud Computing 8.1. Introduction 8.2. Related works 8.3. Algorithm description 8.4. Simulation and performance analysis 8.5. Conclusion and Future Work References Chapter 9 Anomaly detection using class of supervised and unsupervised learning algorithms 9. 1. Introduction 9.2. Adaptive threshold and regression techniques for anomaly detection 9.3. Unsupervised Learning techniques for anomaly detection 9.4. Description of the dataset 9.5 Results and Discussions 9.6. Conclusion References Chapter 10 Improving Support Vector Machine accuracy with Shogun’s multiple kernel learning 10. 1. Introduction 10. 2. Support Vector Machine Statistics 10.3. Experiment and Result 10.4 Conclusion References Chapter 11 An Introduction to Parallelisable String-Based SP-Languages 11.1. Introduction 11.2. Parallelisable string-based SP-languages 11.3. Parallel Regular Expression 11.4. Equivalence of Parallel Regular Expression and Branching Automaton 11.5. Parallelisable String-Based SP-Grammar 11.6. Parallelisable String-Based SP-Parallel Grammar 11.7. Conclusion 11.8. Applications 11.9. Future Scope References Chapter 12 Detection of Disease using Machine Learning 12.1. Introduction 12.2. Techniques Applied 12.3. General architecture of AI/ML 12.4. Experimental outcomes 12.5. Conclusion References Chapter 13 Driver Drowsiness Detection Using Eye Tracing System 13.1. Introduction 13.2. Literature Review 13.3. Research Method 13.4. Observations and Results 13.5. Conclusion References Chapter 14 An Efficient Image Encryption Scheme Combining Rubik Cube Principle with Masking 14.1 Introduction 14.2 Preliminary Section 14.3 Proposed Work 14. 4 Experimental Setup and Simulation Analysis 14.5 Conclusion References


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Product Details
  • ISBN-13: 9781032300146
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 202
  • Weight: 290 gr
  • ISBN-10: 1032300140
  • Publisher Date: 15 Dec 2022
  • Binding: Hardback
  • Language: English
  • Sub Title: Mathematical Modeling and Applications
  • Width: 156 mm


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Neural Networks, Machine Learning, and Image Processing: Mathematical Modeling and Applications
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