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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.

  • 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.
  • 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.
  • 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.
  • 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.
  • Deep Learning in Action: Image and Video Processing for Practical Use

    • 1st Edition
    • Abdussalam Elhanashi + 1 more
    • English
    Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern.
  • Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City

    • 1st Edition
    • Tuan Anh Nguyen
    • English
    In smart cities, information and communication technologies are integrated to exchange real-time data between citizens, governments, and organizations. Blockchain provides security for communication and transactions between multiple stakeholders. Digital twin refers to a simulation of physical products in a virtual space. This simulation fully utilizes the physical models, wireless sensor networks, and historical data of city operation to integrate big information (digital twin cities) under multidiscipline, multiphysical quantities, multiscale, and multiprobability.Dig... Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City explores how digital twins and blockchain can be used in smart cities. Part 1 deals with their promising applications for healthy cities. Part 2 covers other promising applications and current perspectives of blockchain and digital twins for future smart society and smart city mobility. Together with its companion volume, Digital Twin and Blockchain for Sensor Networks in Smart Cities, this book helps to understand the vast amount of data around the city to encourage happy, healthy, safe, and productive lives.
  • Digital Twin and Blockchain for Sensor Networks in Smart Cities

    • 1st Edition
    • Tuan Anh Nguyen
    • English
    Digital twin, blackchain, and wireless sensor networks can work together to improve services in the smart city. Big data derived from wireless sensor networks can be integrated to accommodate the exchange of real-time data between citizens, governments, and organizations. Blockchain can provide high security for large-scale communications and transactions between many stakeholders. Digital twin uses physical models and historical data to integrate big information under multidiscipline, multiphysical quantities, multiscale, and multiprobability conditions.Digital Twin and Blockchain for Sensor Networks in Smart Cities explores how digital twin and blockchain can be optimized to improve services. This book is divided into three parts. Part 1 focuses on the fundamental concepts of blockchain and digital twin for sensor networks in the smart cities, while Part 2 describes their applications for managing the regular operations and services. Part 3 deals with their applications for safe cities.