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A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Divided in...
This collection of proceedings from the International Conference on Systems Engineering, Las Vegas, 2014 is orientated toward systems engineering, including topics like aero-space, power systems, industrial automation and robotics, systems theory, control theory, artificial intelligence, signal processing, decision support, pattern recognition and machine learning, information and communication technologies, image processing, and computer vision as well as its applications. The volume’s main focus is on models, algorithms, and software tools that facilitate efficient and convenient utilization of modern achievements in systems engineering.
This edited volume contains technical contributions in the field of computer vision and image processing presented at the First International Conference on Computer Vision and Image Processing (CVIP 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics – reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-reso...
Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of ma...
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 learn...
Neurodevelopmental disorders encompass a group of conditions that can typically manifest during early childhood. These include intellectual disabilities, communication disorders, autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), specific learning disorder (SLD), and motor disorders. Early identification and assessment can be a valuable tool in determining diagnosis, prognosis, functional abilities, and formulating clinical intervention for both children and adults with neurodevelopmental disorders. Emerging Trends in the Diagnosis and Intervention of Neurodevelopmental Disorders is an essential reference source that discusses and disseminates contributions covering recent trends in diagnosis, assessment, and intervention techniques. Featuring research on topics such as clinical linguistics, neural connectivity, and animal-assisted therapy, this book is ideally designed for speech pathologists, social workers, occupational therapists, psychologists, psychiatrists, neurologists, pediatricians, researchers, clinicians, and academicians seeking coverage on neural and developmental disorder identification and strategies for clinician support and therapies.
In healthcare systems, medical devices help physicians and specialists in diagnosis, prognosis, and therapeutics. As research shows, validation of medical devices is significantly optimized by accurate signal processing. Biomedical Signal and Image Processing in Patient Care is a pivotal reference source for progressive research on the latest development of applications and tools for healthcare systems. Featuring extensive coverage on a broad range of topics and perspectives such as telemedicine, human machine interfaces, and multimodal data fusion, this publication is ideally designed for academicians, researchers, students, and practitioners seeking current scholarly research on real-life technological inventions.
This book will provide an overview of techniques for visual monitoring including video surveillance and human activity understanding. It will present the basic techniques of processing video from static cameras, starting with object detection and tracking. The author will introduce further video analytic modules including face detection, trajectory analysis and object classification. Examining system design and specific problems in visual surveillance, such as the use of multiple cameras and moving cameras, the author will elaborate on privacy issues focusing on approaches where automatic processing can help protect privacy.