Machine Learning Algorithms For Signal And Image Processing

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Machine Learning Algorithms for Signal and Image Processing

Deepika Ghai,Suman Lata Tripathi,Sobhit Saxena,Manash Chanda,Mamoun Alazab
Machine Learning Algorithms for Signal and Image Processing Book PDF

Author : Deepika Ghai,Suman Lata Tripathi,Sobhit Saxena,Manash Chanda,Mamoun Alazab
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 48,8 Mb
Release : 2022-11-18
Category : Technology & Engineering
ISBN : 9781119861843

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Machine Learning Algorithms for Signal and Image Processing by Deepika Ghai,Suman Lata Tripathi,Sobhit Saxena,Manash Chanda,Mamoun Alazab Pdf

Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Deep Learning for Multimedia Processing Applications

Uzair Aslam Bhatti,Huang Mengxing,Jingbing Li,Sibghat Ullah Bazai,Muhammad Aamir
Deep Learning for Multimedia Processing Applications Book PDF

Author : Uzair Aslam Bhatti,Huang Mengxing,Jingbing Li,Sibghat Ullah Bazai,Muhammad Aamir
Publisher : CRC Press
Page : 481 pages
File Size : 42,8 Mb
Release : 2024-02-21
Category : Computers
ISBN : 9781003828051

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Deep Learning for Multimedia Processing Applications by Uzair Aslam Bhatti,Huang Mengxing,Jingbing Li,Sibghat Ullah Bazai,Muhammad Aamir Pdf

Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing. Divided into two volumes, Volume Two delves into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), explaining their unique capabilities in multimedia tasks. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos. Furthermore, the book explores audio processing tasks such as speech recognition, music classification, and sound event detection using deep learning models. It demonstrates how deep learning algorithms can effectively process audio data, opening up new possibilities in multimedia applications. Lastly, the book explores the integration of deep learning with natural language processing techniques, enabling systems to understand, generate, and interpret textual information in multimedia contexts. Throughout the book, practical examples, code snippets, and real-world case studies are provided to help readers gain hands-on experience in implementing deep learning solutions for multimedia processing. Deep Learning for Multimedia Processing Applications is an essential resource for anyone interested in harnessing the power of deep learning to unlock the vast potential of multimedia data.

Hyperspectral Image Analysis

Saurabh Prasad,Jocelyn Chanussot
Hyperspectral Image Analysis Book PDF

Author : Saurabh Prasad,Jocelyn Chanussot
Publisher : Springer Nature
Page : 464 pages
File Size : 50,5 Mb
Release : 2020-04-27
Category : Computers
ISBN : 9783030386177

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Hyperspectral Image Analysis by Saurabh Prasad,Jocelyn Chanussot Pdf

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

Machine Learning in Signal Processing

Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
Machine Learning in Signal Processing Book PDF

Author : Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
Publisher : CRC Press
Page : 488 pages
File Size : 48,7 Mb
Release : 2021-12-10
Category : Technology & Engineering
ISBN : 9781000487817

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Machine Learning in Signal Processing by Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar Pdf

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision

Karm Veer Arya,Ciro Rodriguez,Saurabh Singh,Abhishek Singhal
Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision Book PDF

Author : Karm Veer Arya,Ciro Rodriguez,Saurabh Singh,Abhishek Singhal
Publisher : Unknown
Page : 0 pages
File Size : 49,5 Mb
Release : 2024
Category : Artificial intelligence
ISBN : 1774914689

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Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision by Karm Veer Arya,Ciro Rodriguez,Saurabh Singh,Abhishek Singhal Pdf

"Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision provides in-depth and detailed knowledge about the latest research in image processing and computer vision techniques. It is a roadmap for the improvement of computer vision and image processing, explaining the machine learning algorithms and models involved. The authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides real-world examples to illustrate the concepts and methods. The authors discuss machine learning in healthcare systems for detection, diagnosis, classification, and segmentation. They also explore the diverse applications of image and video processing, including image colorization and restoration using deep learning, using machine learning to record the changes in the Amazon rainforest over time with remote sensing, and more. Researchers, teachers, and students working in the field of artificial intelligence, machine learning, and computer vision will benefit from the knowledge presented here on the diverse applications of computer vision and image processing"--

Signal Processing and Machine Learning for Brain-Machine Interfaces

Toshihisa Tanaka,Mahnaz Arvaneh
Signal Processing and Machine Learning for Brain Machine Interfaces Book PDF

Author : Toshihisa Tanaka,Mahnaz Arvaneh
Publisher : Institution of Engineering and Technology
Page : 355 pages
File Size : 47,8 Mb
Release : 2018-09
Category : Technology & Engineering
ISBN : 9781785613982

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Signal Processing and Machine Learning for Brain-Machine Interfaces by Toshihisa Tanaka,Mahnaz Arvaneh Pdf

This book introduces signal processing and machine learning techniques for Brain Machine Interfacing/Brain Computer Interfacing (BMI/BCI), and their practical and future applications in neuroscience, medicine, and rehabilitation. This is an emerging and challenging technology in engineering, computing, machine learning, neuroscience and medicine, and so the book will interest researchers, engineers, professionals and specialists from all of these areas who need to know more about cutting edge technologies in the fields.

Biomedical Signal and Image Processing with Artificial Intelligence

Chirag Paunwala,Mita Paunwala,Rahul Kher,Falgun Thakkar,Heena Kher,Mohammed Atiquzzaman,Norliza Mohd. Noor
Biomedical Signal and Image Processing with Artificial Intelligence Book PDF

Author : Chirag Paunwala,Mita Paunwala,Rahul Kher,Falgun Thakkar,Heena Kher,Mohammed Atiquzzaman,Norliza Mohd. Noor
Publisher : Springer Nature
Page : 423 pages
File Size : 50,8 Mb
Release : 2023-01-09
Category : Technology & Engineering
ISBN : 9783031158162

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Biomedical Signal and Image Processing with Artificial Intelligence by Chirag Paunwala,Mita Paunwala,Rahul Kher,Falgun Thakkar,Heena Kher,Mohammed Atiquzzaman,Norliza Mohd. Noor Pdf

This book focuses on advanced techniques used for feature extraction, analysis, recognition, and classification in the area of biomedical signal and image processing. Contributions cover all aspects of artificial intelligence, machine learning, and deep learning in the field of biomedical signal and image processing using novel and unexplored techniques and methodologies. The book covers recent developments in both medical images and signals analyzed by artificial intelligence techniques. The authors also cover topics related to development based artificial intelligence, which includes machine learning, neural networks, and deep learning. This book will provide a platform for researchers who are working in the area of artificial intelligence for biomedical applications. Provides insights into medical signal and image analysis using artificial intelligence; Includes novel and recent trends of decision support system for medical research; Outlines employment of evolutionary algorithms for biomedical data, big data analysis for medical databases, and reliability, opportunities, and challenges in clinical data.

Neural Networks, Machine Learning, and Image Processing

Manoj Sahni,Ritu Sahni,Jose M Merigo
Neural Networks Machine Learning and Image Processing Book PDF

Author : Manoj Sahni,Ritu Sahni,Jose M Merigo
Publisher : CRC Press
Page : 221 pages
File Size : 55,7 Mb
Release : 2022-12-15
Category : Computers
ISBN : 9781000814293

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Neural Networks, Machine Learning, and Image Processing by Manoj Sahni,Ritu Sahni,Jose M Merigo Pdf

SECTION I Mathematical Modeling and Neural Network’ Mathematical Essence 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

Machine Learning for Signal Processing

Max A. Little
Machine Learning for Signal Processing Book PDF

Author : Max A. Little
Publisher : Oxford University Press, USA
Page : 378 pages
File Size : 41,5 Mb
Release : 2019
Category : Computers
ISBN : 9780198714934

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Machine Learning for Signal Processing by Max A. Little Pdf

Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Advanced Machine Intelligence and Signal Processing

Deepak Gupta,Koj Sambyo,Mukesh Prasad,Sonali Agarwal
Advanced Machine Intelligence and Signal Processing Book PDF

Author : Deepak Gupta,Koj Sambyo,Mukesh Prasad,Sonali Agarwal
Publisher : Springer Nature
Page : 859 pages
File Size : 46,5 Mb
Release : 2022-06-25
Category : Technology & Engineering
ISBN : 9789811908408

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Advanced Machine Intelligence and Signal Processing by Deepak Gupta,Koj Sambyo,Mukesh Prasad,Sonali Agarwal Pdf

This book covers the latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing, and their applications in real world. The topics covered in machine learning involve feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modeling from video, 3D object recognition, localization and tracking, medical image analysis, and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multitask, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), and electromyogram (EMG).

Learning Approaches in Signal Processing

Wan-Chi Siu,Lap-Pui Chau,Liang Wang,Tieniu Tang
Learning Approaches in Signal Processing Book PDF

Author : Wan-Chi Siu,Lap-Pui Chau,Liang Wang,Tieniu Tang
Publisher : CRC Press
Page : 678 pages
File Size : 42,6 Mb
Release : 2018-12-07
Category : Technology & Engineering
ISBN : 9780429592263

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Learning Approaches in Signal Processing by Wan-Chi Siu,Lap-Pui Chau,Liang Wang,Tieniu Tang Pdf

This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc.

Machine Learning

Anonim
Machine Learning Book PDF

Author : Anonim
Publisher : BoD – Books on Demand
Page : 153 pages
File Size : 54,5 Mb
Release : 2021-12-22
Category : Computers
ISBN : 9781839694844

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Machine Learning by Anonim Pdf

Recent times are witnessing rapid development in machine learning algorithm systems, especially in reinforcement learning, natural language processing, computer and robot vision, image processing, speech, and emotional processing and understanding. In tune with the increasing importance and relevance of machine learning models, algorithms, and their applications, and with the emergence of more innovative uses–cases of deep learning and artificial intelligence, the current volume presents a few innovative research works and their applications in real-world, such as stock trading, medical and healthcare systems, and software automation. The chapters in the book illustrate how machine learning and deep learning algorithms and models are designed, optimized, and deployed. The volume will be useful for advanced graduate and doctoral students, researchers, faculty members of universities, practicing data scientists and data engineers, professionals, and consultants working on the broad areas of machine learning, deep learning, and artificial intelligence.

Cognitive Systems and Signal Processing in Image Processing

Yu-Dong Zhang,Arun Kumar Sangaiah
Cognitive Systems and Signal Processing in Image Processing Book PDF

Author : Yu-Dong Zhang,Arun Kumar Sangaiah
Publisher : Academic Press
Page : 398 pages
File Size : 47,6 Mb
Release : 2021-11-28
Category : Computers
ISBN : 9780323860093

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Cognitive Systems and Signal Processing in Image Processing by Yu-Dong Zhang,Arun Kumar Sangaiah Pdf

Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing. Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time. Presents cognitive signal processing methodologies that are related to challenging image processing application domains Provides the state-of-the-art in cognitive signal processing approaches in the area of big-data image processing Focuses on other technical aspects and alternatives to traditional tools, algorithms and methodologies Discusses various real-time case studies and implemented works

Explainable Machine Learning Models and Architectures

Suman Lata Tripathi,Mufti Mahmud
Explainable Machine Learning Models and Architectures Book PDF

Author : Suman Lata Tripathi,Mufti Mahmud
Publisher : John Wiley & Sons
Page : 277 pages
File Size : 51,9 Mb
Release : 2023-10-03
Category : Computers
ISBN : 9781394185849

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Explainable Machine Learning Models and Architectures by Suman Lata Tripathi,Mufti Mahmud Pdf

EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Machine Learning in Bio Signal Analysis and Diagnostic Imaging Book PDF

Author : Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
Publisher : Academic Press
Page : 345 pages
File Size : 45,6 Mb
Release : 2018-11-30
Category : Science
ISBN : 9780128160879

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Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi Pdf

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains