This book discusses recent advances in wearable technologies and personal monitoring devices, covering topics such as skin contact-based wearables (electrodes), non-contact wearables, the Internet of things (IoT), and signal processing for wearable devices.
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.
This book shows machine learning enthusiasts and practitioners how to get the best of both worlds by deriving Fisher kernels from deep learning models.
Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization.
Handbook of Pediatric Brain Imaging: Methods and Applications presents state-of-the-art research on pediatric brain image acquisition and analysis from a broad range of imaging modalities, including MRI, EEG and MEG.
Handbook of Medical Image Computing and Computer Assisted Intervention presents important advanced methods and state-of-the art research in medical image computing and computer assisted intervention, providing a comprehensive reference on current technical approaches and solutions, while also offering proven algorithms for a variety of essential medical imaging applications.
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.
This book contains the revised selected papers of 4 workshops held in conjunction with the International Conference on High Performance Computing, Networking, Storage and Analysis (SC) in November 2017 in Denver, CO, USA, and in November 2018 in Dallas, TX, USA: the 6th and 7th International Workshop on Extreme-Scale Programming Tools, ESPT 2017 and ESPT 2018, and the 4th and 5th International Workshop on Visual Performance Analysis, VPA 2017 and VPA 2018.
This volume presents several machine intelligence technologies, developed over recent decades, and illustrates how they can be combined in application.
This important text/reference presents the first dedicated review of techniques for contactless 3D fingerprint identification, including novel and previously unpublished research.
A seminal collection of research methodology themes, this two-volume work provides a set of key scholarly developments related to robustness, allowing scholars to advance their knowledge of research methods used outside of their own immediate fields.
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.
This book constitutes the proceedings of the 11th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2020, as well as two challenges: M&Ms - The Multi-Centre, Multi-Vendor, Multi-Disease Segmentation Challenge, and EMIDEC - Automatic Evaluation of Myocardial Infarction from Delayed-Enhancement Cardiac MRI Challenge.
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.
This book constitutes the refereed conference proceedings of the 21st International Conference on the Applications of Evolutionary Computation, EvoApplications 2018, held in Parma, Italy, in April 2018, collocated with the Evo* 2018 events EuroGP, EvoCOP, and EvoMUSART.
The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.
Apply the Processing language to tasks involved in computer vision--tasks such as edge and corner detection, recognition of motion between frames in a video, recognition of objects, matching of feature points and shapes in different frames for tracking purposes, and more.
Build smarter applications with AI capabilities using Microsoft Cognitive Services APIs without much hassleKey FeaturesExplore the Cognitive Services APIs for building machine learning applicationsBuild applications with computer vision, speech recognition, and language processing capabilitiesLearn to implement human-like cognitive intelligence for your applicationsBook DescriptionMicrosoft Cognitive Services is a set of APIs for adding intelligence to your application and leverage the power of AI to solve any business problem using the cognitive capabilities.
Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithmsKey FeaturesLearn about the new features that help unlock the full potential of OpenCV 4Build face detection applications with a cascade classifier using face landmarksCreate an optical character recognition (OCR) model using deep learning and convolutional neural networksBook DescriptionMastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV.
Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical codeKey FeaturesBuild powerful computer vision applications in concise code with OpenCV 4 and Python 3Learn the fundamental concepts of image processing, object classification, and 2D and 3D trackingTrain, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networksBook DescriptionComputer vision is a rapidly evolving science, encompassing diverse applications and techniques.
Get to grips with traditional computer vision algorithms and deep learning approaches, and build real-world applications with OpenCV and other machine learning frameworksKey FeaturesUnderstand how to capture high-quality image data, detect and track objects, and process the actions of animals or humansImplement your learning in different areas of computer visionExplore advanced concepts in OpenCV such as machine learning, artificial neural network, and augmented realityBook DescriptionOpenCV is a native cross-platform C++ library for computer vision, machine learning, and image processing.
Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R librariesKey FeaturesImplement deep learning algorithms to build AI models with the help of tips and tricksUnderstand how deep learning models operate using expert techniquesApply reinforcement learning, computer vision, GANs, and NLP using a range of datasetsBook DescriptionDeep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data.
Visual Computing for Medicine, Second Edition, offers cutting-edge visualization techniques and their applications in medical diagnosis, education, and treatment.
Plan recognition, activity recognition, and intent recognition together combine and unify techniques from user modeling, machine vision, intelligent user interfaces, human/computer interaction, autonomous and multi-agent systems, natural language understanding, and machine learning.
This book constitutes the refereed joint proceedings of the Third International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020.
This book looks at the increasing interest in running microscopy processing algorithms on big image data by presenting the theoretical and architectural underpinnings of a web image processing pipeline (WIPP).
This book reviews the use of digital surveillance for detecting, investigating and interpreting fraud associated with critical cyberinfrastructures in Nigeria, as it is well known that the country's cyberspace and cyberinfrastructures are very porous, leaving too much room for cyber-attackers to freely operate.
Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and KerasKey FeaturesUnderstand the common architecture of different types of GANsTrain, optimize, and deploy GAN applications using TensorFlow and KerasBuild generative models with real-world data sets, including 2D and 3D dataBook DescriptionDeveloping Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand.
Build and train scalable neural network models on various platforms by leveraging the power of Caffe2Key FeaturesMigrate models trained with other deep learning frameworks on Caffe2Integrate Caffe2 with Android or iOS and implement deep learning models for mobile devicesLeverage the distributed capabilities of Caffe2 to build models that scale easilyBook DescriptionCaffe2 is a popular deep learning library used for fast and scalable training and inference of deep learning models on various platforms.
The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.
This book constitutes the refereed post-conference proceedings of 3 workshops, held at the 24th International Conference on Pattern Recognition, Beijing, China, in August 2018: the Third International Workshop on Computer Vision for Analysis of Underwater Imagery, CVAUI 2018, the 7th International Workshop on Computational Forensics, IWCF 2018, and the International Workshop on Multimedia Information Processing for Personality and Social Networks Analysis, MIPPSNA 2018.
The four-volume set LNCS 11070, 11071, 11072, and 11073 constitutes the refereed proceedings of the 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, held in Granada, Spain, in September 2018.
The history of computer-aided face recognition dates to the 1960s, yet the problem of automatic face recognition - a task that humans perform routinely and effortlessly in our daily lives - still poses great challenges, especially in unconstrained conditions.
