Books in Computer vision and pattern recognition

This collection includes research on image analysis, object detection, facial recognition, and pattern analysis. Showcasing state-of-the-art algorithms, practical applications, and case studies, it supports researchers, developers, and students in advancing visual understanding systems. Emphasizing deep learning, biometrics, and real-time processing, these resources enable innovations in security, healthcare, robotics, and multimedia.

Computer Vision
Principles, Algorithms, Applications, Learning
6th Edition
E. R. Davies + 1 more
English
Computer Vision: Principles, Algorithms, Applications, Learning, Sixth Edition clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This new sixth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject.
Digital Signal Processing with MATLAB®
From Fundamentals to AI Applications
1st Edition
Samir I. Abood + 1 more
English
Digital Signal Processing with MATLAB®: From Fundamentals to AI Applications provides coverage of discrete-time signals and systems, and lays out the mathematical fundamentals of digital signal processing (DSP) systems. The book contains a solution to large-scale signal processing problems, namely the development of methods and algorithms that increase (a) operational efficiency under different uncertainty conditions and (b) system stability rate. It offers an algebraic approach to digital signal processing, including algorithms related to digital systems, the setting of parameters, plus operational estimation, detection, classification, resolution, and reliability. Digital Signal Processing with MATLAB®: From Fundamentals to AI Applications begins with a thorough explanation of MATLAB® in recognition of the Accreditation Board for Engineering and Technology (ABET) requirements for integrating computer tools into DSP. The principles of DSP are presented using a step-by-step approach; each chapter starts with an introduction that states the chapter objectives, and ends with a discussion of practical applications of DSP, including providing problems that help the reader understand how the concepts are used in real-life situations. Sometimes, problems are solved in two or three ways to facilitate a deeper understanding and comparison of different approaches. Digital Signal Processing with MATLAB®: From Fundamentals to AI Applications teaches the fundamental principles of digital signal processing, and explains how MATLAB® can be used in the development of methods and algorithms for DSP.
Signal Processing Roadmap
Technologies, Applications, and Future Directions
1st Edition
Pushan Kumar Dutta + 4 more
English
Signal Processing Roadmap: Technologies, Applications, and Future Directions explores cutting-edge and emerging signal-processing techniques across various measurement and monitoring applications, serving as an authoritative reference for engineers, researchers, and technologists. The book critically analyzes key signal processing considerations such as uncertainty modeling that enable more intelligent and reliable next-generation measurement systems, all of which are backed by real-world implementation examples in areas ranging from Internet of Things devices to complex biomedical equipment. In addition, sections provide an overview of the latest research in the hybrid information system modeling field, with a particular emphasis on practical applications in various fields. The book includes case studies and examples of how these models have been used to solve problems in finance, healthcare, engineering, and other related fields. Finally, the book reviews the theories and concepts related to non-linear optimization, fuzzy sets, and rough sets.
Computational Intelligence in Surveillance Systems Using Image Processing
1st Edition
Jay Kumar Pandey + 3 more
English
Traditional surveillance systems struggle to process large volumes of visual data, identify specific objects or behaviors, and adapt to dynamic environments. Computational intelligence, which encompasses techniques like artificial intelligence (AI), machine learning (ML), and computer vision, offers powerful tools to address these challenges by enabling automated analysis, pattern recognition, and decision-making based on visual data. Computational Intelligence in Surveillance Systems Using Image Processing addresses the unique challenges and ethical considerations of applying AI and ML, offering a nuanced understanding of the regulatory landscape. It provides insights into the responsible development and deployment of technologies to unlock the transformative potential of computational intelligence to revolutionize surveillance systems and advance the capabilities of security and monitoring across various sectors.
Smart City Computational Paradigms
A Sustainable Approach
1st Edition
Mohit Kumar + 3 more
English
Smart City Computational Paradigms: A Sustainable Approach describes the connections between state-of-the-art technologies while also providing a comprehensive overview for readers interested in advanced technologies. The smart city paradigm combines smart homes, smart healthcare, smart transportation, smart industry, smart environment, and smart energy to ensure sustainability, well-being, and comfortable living within the urban environment for the city's citizens. The book identifies challenges and proposed solutions and covers underlying theory, design techniques, classification, taxonomy, and analytical tools. Content primarily focuses on real-time applications, uncertainty solutions, and approaches with hands-on demonstrations for decision-making outcomes.This convergence of computational intelligence and IoT not only transforms data into actionable knowledge but also fosters the development of autonomous, efficient, and adaptive systems across diverse domains, ranging from smart cities to healthcare and industrial applications. The integration of computational intelligence with IoT enhances the capabilities of connected systems, making them smarter, more efficient, and better equipped to handle the complexities of the modern world.
Adaptive AI in Sensor Informatics
Methods, Applications, and Implications
1st Edition
Karthik Ramamurthy + 4 more
English
Adaptive AI in Sensor Informatics: Methods, Applications, and Implications explores the growing need for efficient, interpretable, and reliable adaptive AI systems tailored to wireless sensor networks. The book highlights how adaptive AI strengthens collaboration between humans and artificial intelligence by enabling transparent decision-making processes. Aimed at academics, professionals, and students, it provides an accessible yet thorough guide to understanding the intersection of adaptive AI and sensor informatics, focusing on practical implementation and the development of models that are both trustworthy and user-friendly. Readers will gain insight into the essential role adaptive AI plays in advancing wireless sensor networks across various sectors.The book also examines the unique challenges and opportunities that arise when deploying adaptive AI in real-world sensor environments. It offers actionable advice for designing AI models that comply with regulations and support user confidence, especially in areas such as healthcare, environmental monitoring, smart cities, and industrial automation.
Advances in Image Processing, Reliability, and Artificial Intelligence
Data Centred-Techniques and Applications in Edge Computing
1st Edition
Mario J. Divan + 4 more
English
Advances in Image Processing, Reliability, and Artificial Intelligence: Data Centred-Techniques and Applications in Edge Computing provides a clear outlook of the mechanisms, risks, challenges, and opportunities in system reliability for image processing and AI applications running on edge devices. It provides Best Known Configuration (BKC) and Methods (BKM) while discussing trends and future works based on current research. The content serves as a reference for practitioners and provides a state-of-the-art for researchers in the area. It provides foundations to analyse and replicate different applications through use cases. It tackles concerns for how reliability aspects (i.e., fault tolerance, availability, maturity, and recoverability) are addressed for applications running in an environment that is not fully controlled and exposed to environmental variations.
Feature Extraction and Image Processing for Computer Vision
5th Edition
Mark Nixon + 1 more
English
Feature Extraction and Image Processing for Computer Vision, Fifth Edition is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated, providing a link between theory and implementation. Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.
Quaternion-Based Sparse Image Processing
Advances in Multispectral Processing
1st Edition
Satya Prakash Yadav + 4 more
English
Quaternion-Sparse Image Processing: Advances in Multispectral Processing brings together the technologies, research, and managerial applications of quaternion-sparse based complex algebra in image processing. The book covers the entire range of complicated tasks performed on color images, including denoising, reconstruction, classification, hallucination, feature extraction, dimension reduction, and regularization. It provides easy understanding and smooth adaptability of basic and advanced concepts for graduate students, researchers, doctors, academics, and practitioners.
Sensor Networks for Smart Hospitals
1st Edition
Tuan Anh Nguyen
English
Sensor Networks for Smart Hospitals shows how the use of sensors to gather data on a patient's condition and the environment in which their care takes place can allow healthcare professionals to monitor well-being and make informed decisions about treatment. Written by experts in the field, this book is an invaluable resource for researchers and healthcare practitioners in their drive to use technology to improve the lives of patients. Data from sensor networks via the smart hospital framework is comprised of three main layers: data, insights, and access.Medical data is collected in real-time from an array of intelligent devices/systems deployed within the hospital. This data offers insight from the analytics or machine learning software that is accessible to healthcare staff via a smartphone or mobile device to facilitate swifter decisions and greater efficiency.
Computational Knowledge Vision
The First Footprints
1st Edition
Wenbo Zheng + 1 more
English
Computational Knowledge Vision: The First Footprints presents a novel, advanced framework which combines structuralized knowledge and visual models. In advanced image and visual perception studies, a visual model's understanding and reasoning ability often determines whether it works well in complex scenarios. This book presents state-of-the-art mainstream vision models for visual perception. As computer vision is one of the key gateways to artificial intelligence and a significant component of modern intelligent systems, this book delves into computer vision systems that are highly specialized and very limited in their ability to do visual reasoning and causal inference.Questions naturally arise in this arena, including (1) How can human knowledge be incorporated with visual models? (2) How does human knowledge promote the performance of visual models? To address these problems, this book proposes a new framework for computer vision–computational knowledge vision.
Iris and Periocular Recognition using Deep Learning
1st Edition
Ajay Kumar
English
Iris and Periocular Recognition using Deep Learning systematically explains the fundamental and most advanced techniques for ocular imprint-based human identification, with many applications in sectors such as healthcare, online education, e-business, metaverse, and entertainment. This is the first-ever book devoted to iris recognition that details cutting-edge techniques using deep neural networks. This book systematically introduces such algorithmic details with attractive illustrations, examples, experimental comparisons, and security analysis. It answers many fundamental questions about the most effective iris and periocular recognition techniques.
Intelligent Fractal-Based Image Analysis
Applications in Pattern Recognition and Machine Vision
1st Edition
Soumya Ranjan Nayak + 3 more
English
Intelligent Fractal-Based Image Analysis: Application in Pattern Recognition and Machine Vision provides insights into the current strengths and weaknesses of different applications as well as research findings on fractal graphics in engineering and science applications. The book aims to improve the exchange of ideas and coherence between various core computing methods and highlights the relevance of related application areas for advanced as well as novice-user application. The book presents core concepts, methodological aspects, and advanced feature opportunities, focusing on major, real-time applications in engineering and health science. It will appeal to researchers, data scientists, industry professionals, and graduate students.Fractals are infinite, complex patterns used in modeling physical and dynamic systems. Fractal theory research has increased across different fields of applications including engineering science, health science, and social science. Recent literature shows the vital role fractals play in digital image analysis, specifically in biomedical image processing. Fractal graphics is an interdisciplinary field that deals with how computers can be used to gain high-level understanding from digital images. Integrating artificial intelligence with fractal characteristics has resulted in new interdisciplinary research in the fields of pattern recognition and image processing analysis.
Intelligent Algorithms
Theory and Practice
1st Edition
Han Huang + 1 more
English
Intelligent Algorithms: Theory and Practice discusses the latest achievements of the computation time analysis theory and practical applications of intelligent algorithms. In five chapters, the book covers (1) New methods of intelligent algorithm computation time analysis; (2)Application of intelligent algorithms in computer vision; (3) Application of intelligent algorithms in logistics scheduling; (4) Application of intelligent algorithms in software testing; and (5) Application of intelligent algorithm in multi-objective optimization.The content of each chapter is supported by papers published in top journals. The book's authors introduce the work of each part, which mainly includes a brief introduction (mainly for readers to understand) and academic discussion (rigorous theoretical and experimental support), in a vivid and interesting way through excellent pictures and literary compositions. To help readers learn and make progress together, each part of this book provides relevant literature, code, experimental data, and so on.
Machine Learning with Noisy Labels
Definitions, Theory, Techniques and Solutions
1st Edition
Gustavo Carneiro
English
Machine Learning and Noisy Labels: Definitions, Theory, Techniques and Solutions provides an ideal introduction to machine learning with noisy labels that is suitable for senior undergraduates, post graduate students, researchers and practitioners using, and researching, machine learning methods. Most of the modern machine learning models based on deep learning techniques depend on carefully curated and cleanly labeled training sets to be reliably trained and deployed. However, the expensive labeling process involved in the acquisition of such training sets limits the number and size of datasets available to build new models, slowing down progress in the field. This book defines the different types of label noise, introduces the theory behind the problem, presents the main techniques that enable the effective use of noisy-label training sets, and explains the most accurate methods.
Engineering Simulation and its Applications
Algorithms and Numerical Methods
1st Edition
Xin-She Yang
English
Engineering Simulation and its Applications: Algorithms and Numerical Methods covers the essential quantitative methods needed for engineering simulations, introducing optimization techniques that can be used in the design of systems to minimize cost and maximize efficiency. This book serves as a reference and textbook for courses such as engineering simulation, design optimization, mathematical modeling, numerical methods, data analysis, and engineering management. Diverse coverage of the various subject areas within the field puts the essential topics into a single book for easy access for graduates and senior undergraduates. It also serves as a reference book for lecturers and industrial practitioners.
High-Order Models in Semantic Image Segmentation
1st Edition
Ismail Ben Ayed
English
High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging.
Visualization, Visual Analytics and Virtual Reality in Medicine
State-of-the-art Techniques and Applications
1st Edition
Bernhard Preim + 3 more
English
Visualization, Visual Analytics and Virtual Reality in Medicine: State-of-the-art Techniques and Applications describes important techniques and applications that show an understanding of actual user needs as well as technological possibilities. The book includes user research, for example, task and requirement analysis, visualization design and algorithmic ideas without going into the details of implementation. This reference will be suitable for researchers and students in visualization and visual analytics in medicine and healthcare, medical image analysis scientists and biomedical engineers in general. Visualization and visual analytics have become prevalent in public health and clinical medicine, medical flow visualization, multimodal medical visualization and virtual reality in medical education and rehabilitation. Relevant applications now include digital pathology, virtual anatomy and computer-assisted radiation treatment planning.
Biomedical Image Synthesis and Simulation
Methods and Applications
1st Edition
Ninon Burgos + 1 more
English
Biomedical Image Synthesis and Simulation: Methods and Applications presents the basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. The first part of the book introduces and describes the simulation and synthesis methods that were developed and successfully used within the last twenty years, from parametric to deep generative models. The second part gives examples of successful applications of these methods. Both parts together form a book that gives the reader insight into the technical background of image synthesis and how it is used, in the particular disciplines of medical and biomedical imaging. The book ends with several perspectives on the best practices to adopt when validating image synthesis approaches, the crucial role that uncertainty quantification plays in medical image synthesis, and research directions that should be worth exploring in the future.
Advanced Methods and Deep Learning in Computer Vision
1st Edition
E. R. Davies + 1 more
English
Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students.
Deep Learning Models for Medical Imaging
1st Edition
KC Santosh + 2 more
English
Deep Learning Models for Medical Imaging explains the concepts of Deep Learning (DL) and its importance in medical imaging and/or healthcare using two different case studies: a) cytology image analysis and b) coronavirus (COVID-19) prediction, screening, and decision-making, using publicly available datasets in their respective experiments. Of many DL models, custom Convolutional Neural Network (CNN), ResNet, InceptionNet and DenseNet are used. The results follow ‘with’ and ‘without’ transfer learning (including different optimization solutions), in addition to the use of data augmentation and ensemble networks. DL models for medical imaging are suitable for a wide range of readers starting from early career research scholars, professors/scientist... to industrialists.
Computer-Aided Oral and Maxillofacial Surgery
Developments, Applications, and Future Perspectives
1st Edition
Jan Egger + 1 more
English
Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery. In facial surgery, computer-aided decisions supplement all kind of treatment stages, from a diagnosis to follow-up examinations. This book gives an in-depth overview of state-of-the-art technologies, such as deep learning, augmented reality, virtual reality and intraoperative navigation, as applied to oral and maxillofacial surgery. It covers applications of facial surgery that are at the interface between medicine and computer science. Examples include the automatic segmentation and registration of anatomical and pathological structures, like tumors in the facial area, intraoperative navigation in facial surgery and its recent developments and challenges for treatments like zygomatic implant placement.
Computer Vision for Microscopy Image Analysis
1st Edition
Mei Chen
English
Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts.Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The main challenge and bottleneck in such experiments is the conversion of "big visual data" into interpretable information.Visual analysis of large-scale microscopy data is a daunting task. Computer vision has the potential to automate this task. One key advantage is that computers perform analysis more reproducibly and less subjectively than human annotators. Moreover, high-throughput microscopy calls for effective and efficient techniques as there are not enough human resources to advance science by manual annotation.This book articulates the strong need for biologists and computer vision experts to collaborate to overcome the limits of human visual perception, and devotes a chapter each to the major steps in analyzing microscopy images, such as detection and segmentation, classification, tracking, and event detection.
Quantitative Magnetic Resonance Imaging
1st Edition
Volume 1
Nicole Seiberlich + 6 more
English
Quantitative Magnetic Resonance Imaging is a ‘go-to’ reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion.Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: The basic physics behind tissue property mapping How to implement basic pulse sequences for the quantitative measurement of tissue properties The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* The pros and cons for different approaches to mapping perfusion The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor maps and more complex representations of diffusion How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance Fingerprinting can be used to accelerate or improve tissue property mapping schemes How tissue property mapping is used clinically in different organs
OpenVX Programming Guide
1st Edition
Frank Brill + 3 more
English
OpenVX is the computer vision API adopted by many high-performance processor vendors. It is quickly becoming the preferred way to write fast and power-efficient code on embedded systems. OpenVX Programming Guidebook presents definitive information on OpenVX 1.2 and 1.3, the Neural Network, and other extensions as well as the OpenVX Safety Critical standard. This book gives a high-level overview of the OpenVX standard, its design principles, and overall structure. It covers computer vision functions and the graph API, providing examples of usage for the majority of the functions. It is intended both for the first-time user of OpenVX and as a reference for experienced OpenVX developers.
Hybrid Computational Intelligence
Challenges and Applications
1st Edition
Siddhartha Bhattacharyya + 3 more
English
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems.
Feature Extraction and Image Processing for Computer Vision
4th Edition
Mark Nixon + 1 more
English
Feature Extraction for Image Processing and Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the link between theory and exemplar code of the algorithms." Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.
Vision Models for High Dynamic Range and Wide Colour Gamut Imaging
Techniques and Applications
1st Edition
Marcelo Bertalmío
English
To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies.
Spectral Geometry of Shapes
Principles and Applications
1st Edition
Jing Hua + 2 more
English
Spectral Geometry of Shapes presents unique shape analysis approaches based on shape spectrum in differential geometry. It provides insights on how to develop geometry-based methods for 3D shape analysis. The book is an ideal learning resource for graduate students and researchers in computer science, computer engineering and applied mathematics who have an interest in 3D shape analysis, shape motion analysis, image analysis, medical image analysis, computer vision and computer graphics. Due to the rapid advancement of 3D acquisition technologies there has been a big increase in 3D shape data that requires a variety of shape analysis methods, hence the need for this comprehensive resource.
Riemannian Geometric Statistics in Medical Image Analysis
1st Edition
Xavier Pennec + 2 more
English
Over the past 15 years, there has been a growing need in the medical image computing community for principled methods to process nonlinear geometric data. Riemannian geometry has emerged as one of the most powerful mathematical and computational frameworks for analyzing such data. Riemannian Geometric Statistics in Medical Image Analysis is a complete reference on statistics on Riemannian manifolds and more general nonlinear spaces with applications in medical image analysis. It provides an introduction to the core methodology followed by a presentation of state-of-the-art methods. Beyond medical image computing, the methods described in this book may also apply to other domains such as signal processing, computer vision, geometric deep learning, and other domains where statistics on geometric features appear. As such, the presented core methodology takes its place in the field of geometric statistics, the statistical analysis of data being elements of nonlinear geometric spaces. The foundational material and the advanced techniques presented in the later parts of the book can be useful in domains outside medical imaging and present important applications of geometric statistics methodology Content includes: The foundations of Riemannian geometric methods for statistics on manifolds with emphasis on concepts rather than on proofs Applications of statistics on manifolds and shape spaces in medical image computing Diffeomorphic deformations and their applications As the methods described apply to domains such as signal processing (radar signal processing and brain computer interaction), computer vision (object and face recognition), and other domains where statistics of geometric features appear, this book is suitable for researchers and graduate students in medical imaging, engineering and computer science.
Deep Learning through Sparse and Low-Rank Modeling
1st Edition
Zhangyang Wang + 2 more
English
Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models—those that emphasize problem-specific Interpretability—wit... recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics.
Multimodal Behavior Analysis in the Wild
Advances and Challenges
1st Edition
Xavier Alameda-Pineda + 2 more
English
Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing.
Computer Vision for Assistive Healthcare
1st Edition
Leo Marco + 1 more
English
Computer Vision for Assistive Healthcare describes how advanced computer vision techniques provide tools to support common human needs, such as mental functioning, personal mobility, sensory functions, daily living activities, image processing, pattern recognition, machine learning and how language processing and computer graphics cooperate with robotics to provide such tools. Users will learn about the emerging computer vision techniques for supporting mental functioning, algorithms for analyzing human behavior, and how smart interfaces and virtual reality tools lead to the development of advanced rehabilitation systems able to perform human action and activity recognition. In addition, the book covers the technology behind intelligent wheelchairs, how computer vision technologies have the potential to assist blind people, and about the computer vision-based solutions recently employed for safety and health monitoring.
Computer Vision
Principles, Algorithms, Applications, Learning
5th Edition
E. R. Davies
English
Computer Vision: Principles, Algorithms, Applications, Learning (previously entitled Computer and Machine Vision) clearly and systematically presents the basic methodology of computer vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This fully revised fifth edition has brought in more of the concepts and applications of computer vision, making it a very comprehensive and up-to-date text suitable for undergraduate and graduate students, researchers and R&D engineers working in this vibrant subject. See an interview with the author explaining his approach to teaching and learning computer vision - http://scitechconnec...
Imaging Genetics
1st Edition
Adrian Dalca + 3 more
English
Imaging Genetics presents the latest research in imaging genetics methodology for discovering new associations between imaging and genetic variables, providing an overview of the state-of the-art in the field. Edited and written by leading researchers, this book is a beneficial reference for students and researchers, both new and experienced, in this growing area. The field of imaging genetics studies the relationships between DNA variation and measurements derived from anatomical or functional imaging data, often in the context of a disorder. While traditional genetic analyses rely on classical phenotypes like clinical symptoms, imaging genetics can offer richer insights into underlying, complex biological mechanisms.
Biomedical Texture Analysis
Fundamentals, Tools and Challenges
1st Edition
Adrien Depeursinge + 2 more
English
Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images.
Low-Rank Models in Visual Analysis
Theories, Algorithms, and Applications
1st Edition
Zhouchen Lin + 1 more
English
Low-Rank Models in Visual Analysis: Theories, Algorithms, and Applications presents the state-of-the-art on low-rank models and their application to visual analysis. It provides insight into the ideas behind the models and their algorithms, giving details of their formulation and deduction. The main applications included are video denoising, background modeling, image alignment and rectification, motion segmentation, image segmentation and image saliency detection. Readers will learn which Low-rank models are highly useful in practice (both linear and nonlinear models), how to solve low-rank models efficiently, and how to apply low-rank models to real problems.
Discrete-Time Neural Observers
Analysis and Applications
1st Edition
Alma Y Alanis + 1 more
English
Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their application in meaningful areas, such as electric three phase induction motors and anaerobic process, which show the applicability of such designs. The proposed schemes can be employed for different applications beyond those presented. The book presents solutions for the state estimation problem of unknown nonlinear systems based on two schemes. For the first one, a full state estimation problem is considered; the second one considers the reduced order case with, and without, the presence of unknown delays. Both schemes are developed in discrete-time using recurrent high order neural networks in order to design the neural observers, and the online training of the respective neural networks is performed by Kalman Filtering.
Human Recognition in Unconstrained Environments
Using Computer Vision, Pattern Recognition and Machine Learning Methods for Biometrics
1st Edition
Maria De Marsico + 2 more
English
Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data
Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting
1st Edition
Simone Balocco + 4 more
English
Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting.
Multi-Dimensional Summarization in Cyber-Physical Society
1st Edition
Hai Zhuge
English
Text summarization has been studied for over a half century, but traditional methods process texts empirically and neglect the fundamental characteristics and principles of language use and understanding. Automatic summarization is a desirable technique for processing big data. This reference summarizes previous text summarization approaches in a multi-dimensional category space, introduces a multi-dimensional methodology for research and development, unveils the basic characteristics and principles of language use and understanding, investigates some fundamental mechanisms of summarization, studies dimensions on representations, and proposes a multi-dimensional evaluation mechanism. Investigation extends to incorporating pictures into summary and to the summarization of videos, graphs and pictures, and converges to a general summarization method. Further, some basic behaviors of summarization are studied in the complex cyber-physical-socia... space. Finally, a creative summarization mechanism is proposed as an effort toward the creative summarization of things, which is an open process of interactions among physical objects, data, people, and systems in cyber-physical-socia... space through a multi-dimensional lens of semantic computing. The author’s insights can inspire research and development of many computing areas.
Learning-Based Local Visual Representation and Indexing
1st Edition
Rongrong Ji + 4 more
English
Learning-Based Local Visual Representation and Indexing, reviews the state-of-the-art in visual content representation and indexing, introduces cutting-edge techniques in learning based visual representation, and discusses emerging topics in visual local representation, and introduces the most recent advances in content-based visual search techniques.
Face Detection and Recognition on Mobile Devices
1st Edition
Haowei Liu
English
This hands-on guide gives an overview of computer vision and enables engineers to understand the implications and challenges behind mobile platform design choices. Using face-related algorithms as examples, the author surveys and illustrates how design choices and algorithms can be geared towards developing power-saving and efficient applications on resource constrained mobile platforms.
Progress in Pattern Recognition 1
1st Edition
L.N. Kanal + 1 more
English
Progress in Pattern Recognition, Volume 1 focuses on the processes, techniques, and approaches involved in pattern recognition, including conceptual clustering, cross-correlation, syntax, software, data structures, and distance transforms. The selection first tackles progress in syntactic pattern recognition and clustering objects into classes characterized by conjunctive concepts. Discussions focus on an overview of clustering problems, conjunctive conceptual clustering, primitive selection and pattern grammars, high dimensional grammars for pattern description, syntactic pattern recognition using stochastic languages, and syntactic approach to shape and texture analysis. The text then elaborates on database representations in hierarchical scene analysis and medium level vision. The book examines image processing software and analysis and synthesis of image patterns by spatial interaction models. Topics include synopsis of discrete spatial interaction models, nonrecursive models over infinite lattices, finite lattice models, and the MSFC image processing package. The text also reviews the mathematical aspects of image reconstruction from projection and recognition of stereo-image cross-correlation errors. The selection is a highly recommended source of data for researchers interested in the process of pattern recognition.
Digital Picture Processing
2nd Edition
Volume 2
Azriel Rosenfeld
English
Computer Science and Applied Mathematics: Digital Picture Processing, Second Edition, Volume 2 focuses on picture or image processing, which is concerned with the manipulation and analysis of pictures by computer. This book emphasizes the three major subareas in picture processing—digitizat... and compression; enhancement, restoration, and reconstruction; and matching, description, and recognition. This volume is organized into four chapters. Chapter 9 discusses registration and matching, while Chapter 10 considers segmentation into parts. The representation of parts and geometric property measurement is elaborated in Chapter 11. The last chapter is devoted to the non-geometric properties, picture descriptions, and models for classes of pictures. This publication is suitable for specialists and professionals working in the field of digital picture processing.
Pattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems
1st Edition
Volume 16
E.S. Gelsema + 1 more
English
The era of detailed comparisons of the merits of techniques of pattern recognition and artificial intelligence and of the integration of such techniques into flexible and powerful systems has begun.So confirm the editors of this fourth volume of Pattern Recognition in Practice, in their preface to the book.The 42 quality papers are sourced from a broad range of international specialists involved in developing pattern recognition methodologies and those using pattern recognition techniques in their professional work. The publication is divided into six sections: Pattern Recognition, Signal and Image Processing, Probabilistic Reasoning, Neural Networks, Comparative Studies, and Hybrid Systems, giving prospective users a feeling for the applicability of the various methods in their particular field of specialization.
Pattern Recognition and Artificial Intelligence, Towards an Integration
Proceedings of an International Workshop held in Amsterdam, May 18-20, 1988
1st Edition
Volume 7
L.N. Kanal + 1 more
English
This volume brings together the results of research into the methodology and applications of pattern recognition, with particular emphasis given to the incorporation of artificial intelligence methodologies into pattern recognition systems.The first part of this volume covers image analysis and processing software, systems and algorithms. Pattern analysis and classifier design are dealt with in part two, while the last part deals with model based and expert systems, including uncertainty calculus methods in pattern analysis and object recognition. A number of specific application areas are considered, including such diverse topics as fingerprinting, astronomy, molecular biology and pathology.
The Art of Technical Documentation
1st Edition
Katherine Haramundanis
English
The Art of Technical Documentation presents concepts, techniques, and practices in order to produce effective technical documentation. The book provides the definition of technical documentation; qualities of a good technical documentation; career paths and documentation management styles; precepts of technical documentation; practices for gathering information, understanding what you have gathered, and methods for testing documentation; and considerations of information representation, to provide insights on how different representations affect reader perception of your documents. Technical writers and scientists will find the book a good reference material.
Image Modeling
1st Edition
Azriel Rosenfeld
English
Image Modeling compiles papers presented at a workshop on image modeling in Rosemont, Illinois on August 6-7, 1979. This book discusses the mosaic models for textures, image segmentation as an estimation problem, and comparative analysis of line-drawing modeling schemes. The statistical models for the image restoration problem, use of Markov random fields as models of texture, and mathematical models of graphics are also elaborated. This text likewise covers the univariate and multivariate random field models for images, stochastic image models generated by random tessellations of the plane, and long crested wave models. Other topics include the Boolean model and random sets, structural basis for image description, and structure in co-occurrence matrices for texture analysis. This publication is useful to specialists and professionals working in the field of image processing.
Radiosity and Realistic Image Synthesis
1st Edition
Michael F. Cohen + 1 more
English
The goal of image synthesis is to create, using the computer, a visual experience that is identical to what a viewer would experience when viewing a real environment. Radiosity and Realistic Image Synthesis offers the first comprehensive look at the radiosity method for image synthesis and the tools required to approach this elusive goal. Basic concepts and mathematical fundamentals underlying image synthesis and radiosity algorithms are covered thoroughly. (A basic knowledge of undergraduate calculus is assumed). The algorithms that have been developed to implement the radiosity method ranging from environment subdivision to final display are discussed. Successes and difficulties in implementing and using these algorithms are highlighted. Extensions to the basic radiosity method to include glossy surfaces, fog or smoke, and realistic light sources are also described. There are 16 pages of full colour images and over 100 illustrations to explain the development and show the results of the radiosity method. Results of applications of this new technology from a variety of fields are also included.Michael Cohen has worked in the area of realistic image synthesis since 1983 and was instrumental in the development of the radiosity method. He is currently an assistant professor of computer science at Princeton University. John Wallace is a software engineer at 3D/EYE, Inc., where he is the project leader for the development of Hewlett-Packard's ATRCore radiosity and ray tracing library. A chapter on the basic concepts of image synthesis is contributed by Patrick Hanrahan. He has worked on the topic of image synthesis at Pixar, where he was instrumental in the development of the Renderman software. He has also led research on the hierarchical methods at Princeton University, where he is an associate professor of computer science. All three authors have written numerous articles on radiosity that have appeared in the SIGGAPH proceedings and elsewhere. They have also taught the SIGGRAPH course on radiosity for 5 years.