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Reinforcement Learning For Adaptive Sampling In X Ray Applications
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Book Synopsis Reinforcement Learning for Adaptive Sampling in X-ray Applications by : Jean-Raymond Melingui Betterton
Download or read book Reinforcement Learning for Adaptive Sampling in X-ray Applications written by Jean-Raymond Melingui Betterton and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose adaptive sampling algorithms for automating image sampling in scientific x-ray applications. In these applications, we query measurements from various functions of an image in order to estimate it. Since collecting samples is expensive both in terms of time, human resources, and the cost of operating machinery, our goal is to produce autonomous, adaptive sampling methods that attempt to optimize some tradeoff between cost and quality of image estimation, based on information gained from previous measurements. In order to accomplish this, we propose a general methodology that uses reinforcement learning to train autonomous, image-sampling policies that optimize our objective.
Book Synopsis Machine Learning Hybridization and Optimization for Intelligent Applications by : Tanvir Habib Sardar
Download or read book Machine Learning Hybridization and Optimization for Intelligent Applications written by Tanvir Habib Sardar and published by CRC Press. This book was released on 2024-10-28 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using case study-based applications. • Covers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computing. • Explains computing models using real-world examples and dataset-based experiments. • Includes case study-based explanations and usage for machine learning technologies and applications. This book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
Book Synopsis Artificial Intelligence by : Lu Fang
Download or read book Artificial Intelligence written by Lu Fang and published by Springer Nature. This book was released on 2022-12-16 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNCS 13604-13606 constitutes revised selected papers presented at the Second CAAI International Conference on Artificial Intelligence, held in Beijing, China, in August 2022. CICAI is a summit forum in the field of artificial intelligence and the 2022 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 164 papers were thoroughly reviewed and selected from 521 submissions. CICAI aims to establish a global platform for international academic exchange, promote advanced research in AI and its affiliated disciplines such as machine learning, computer vision, natural language, processing, and data mining, amongst others.
Book Synopsis Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning by : Segall, Richard S.
Download or read book Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning written by Segall, Richard S. and published by IGI Global. This book was released on 2022-01-07 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: During these uncertain and turbulent times, intelligent technologies including artificial neural networks (ANN) and machine learning (ML) have played an incredible role in being able to predict, analyze, and navigate unprecedented circumstances across a number of industries, ranging from healthcare to hospitality. Multi-factor prediction in particular has been especially helpful in dealing with the most current pressing issues such as COVID-19 prediction, pneumonia detection, cardiovascular diagnosis and disease management, automobile accident prediction, and vacation rental listing analysis. To date, there has not been much research content readily available in these areas, especially content written extensively from a user perspective. Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning is designed to cover a brief and focused range of essential topics in the field with perspectives, models, and first-hand experiences shared by prominent researchers, discussing applications of artificial neural networks (ANN) and machine learning (ML) for biomedical and business applications and a listing of current open-source software for neural networks, machine learning, and artificial intelligence. It also presents summaries of currently available open source software that utilize neural networks and machine learning. The book is ideal for professionals, researchers, students, and practitioners who want to more fully understand in a brief and concise format the realm and technologies of artificial neural networks (ANN) and machine learning (ML) and how they have been used for prediction of multi-disciplinary research problems in a multitude of disciplines.
Book Synopsis Deep Learning for Biomedical Image Reconstruction by : Jong Chul Ye
Download or read book Deep Learning for Biomedical Image Reconstruction written by Jong Chul Ye and published by Cambridge University Press. This book was released on 2023-09-30 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. Including interdisciplinary examples and a step-by-step background of deep learning, this book provides insight into the future of biomedical image reconstruction with clinical studies and mathematical theory.
Book Synopsis Intelligent Systems Design and Applications by : Ajith Abraham
Download or read book Intelligent Systems Design and Applications written by Ajith Abraham and published by Springer Nature. This book was released on with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Deep Learning for Biomedical Applications by : Utku Kose
Download or read book Deep Learning for Biomedical Applications written by Utku Kose and published by CRC Press. This book was released on 2021-07-19 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, image processing perspectives, and even genomics. It takes the reader through different sides of Deep Learning oriented solutions. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educations who are working in the context of the topics.
Book Synopsis Computer Analysis of Images and Patterns by : Nicolas Tsapatsoulis
Download or read book Computer Analysis of Images and Patterns written by Nicolas Tsapatsoulis and published by Springer Nature. This book was released on 2021-10-30 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set LNCS 13052 and 13053 constitutes the refereed proceedings of the 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021, held virtually, in September 2021. The 87 papers presented were carefully reviewed and selected from 129 submissions. The papers are organized in the following topical sections across the 2 volumes: 3D vision, biomedical image and pattern analysis; machine learning; feature extractions; object recognition; face and gesture, guess the age contest, biometrics, cryptography and security; and segmentation and image restoration.
Book Synopsis Innovations in Multivariate Statistical Modeling by : Andriëtte Bekker
Download or read book Innovations in Multivariate Statistical Modeling written by Andriëtte Bekker and published by Springer Nature. This book was released on 2022-12-15 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary advances, with its core inferential genesis remaining in that of statistics. It is exactly this varied evolution caused by an influx in data production, diffusion, and understanding in scientific fields that has blurred many lines between disciplines. The cross-pollination between statistics and biology, engineering, medical science, computer science, and even art, has accelerated the vast amount of questions that statistical methodology has to answer and report on. These questions are often multivariate in nature, hoping to elucidate uncertainty on more than one aspect at the same time, and it is here where statistical thinking merges mathematical design with real life interpretation for understanding this uncertainty. Statistical advances benefit from these algebraic inventions and expansions in the multivariate paradigm. This contributed volume aims to usher novel research emanating from a multivariate statistical foundation into the spotlight, with particular significance in multidisciplinary settings. The overarching spirit of this volume is to highlight current trends, stimulate a focus on, and connect multidisciplinary dots from and within multivariate statistical analysis. Guided by these thoughts, a collection of research at the forefront of multivariate statistical thinking is presented here which has been authored by globally recognized subject matter experts.
Book Synopsis Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention by : Luping Zhou
Download or read book Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention written by Luping Zhou and published by Springer Nature. This book was released on 2019-11-20 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2019, the First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, HAL-MICCAI 2019, and the Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 8 papers presented at LABELS 2019, the 5 papers presented at HAL-MICCAI 2019, and the 3 papers presented at CuRIOUS 2019 were carefully reviewed and selected from numerous submissions. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing. The HAL-MICCAI papers cover a wide set of hardware applications in medical problems, including medical image segmentation, electron tomography, pneumonia detection, etc. The CuRIOUS papers provide a snapshot of the current progress in the field through extended discussions and provide researchers an opportunity to characterize their image registration methods on newly released standardized datasets of iUS-guided brain tumor resection.
Book Synopsis Handbook of Deep Learning in Biomedical Engineering and Health Informatics by : E. Golden Julie
Download or read book Handbook of Deep Learning in Biomedical Engineering and Health Informatics written by E. Golden Julie and published by CRC Press. This book was released on 2021-09-22 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat patients more effectively. Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. This volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc. Key features: Introduces important recent technological advancements in the field Describes the various techniques, platforms, and tools used in biomedical deep learning systems Includes informative case studies that help to explain the new technologies Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.
Book Synopsis Concepts and Real-Time Applications of Deep Learning by : Smriti Srivastava
Download or read book Concepts and Real-Time Applications of Deep Learning written by Smriti Srivastava and published by Springer Nature. This book was released on 2021-09-23 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields. Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures; Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies; Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.
Book Synopsis Importance Sampling for Reinforcement Learning with Multiple Objectives by : Christian Robert Shelton
Download or read book Importance Sampling for Reinforcement Learning with Multiple Objectives written by Christian Robert Shelton and published by . This book was released on 2001 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis considers three complications that arise from applying reinforcement learning to a real-world application. In the process of using reinforcement learning to build an adaptive electronic market-maker, we find the sparsity of data, the partial observability of the domain, and the multiple objectives of the agent to cause serious problems for existing reinforcement learning algorithms. We employ importance sampling (likelihood ratios) to achieve good performance in partially observable Nlarkov decision processes with few data. Our importance sampling estimator requires no knowledge about the environment and places few restrictions on the method of collecting data. It can be used efficiently with reactive controllers, finite-state controllers, or policies with function approximation. We present theoretical analyses of the estimator and incorporate it into a reinforcement learning algorithm. Additionally, this method provides a complete return surface which can be used to balance multiple objectives dynamically. We demonstrate the need for multiple goals in a variety of applications and natural solutions based on our sampling method. The thesis concludes with example results from employing our algorithm to the domain of automated electronic market-making.
Book Synopsis Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes) by :
Download or read book Handbook On Big Data And Machine Learning In The Physical Sciences (In 2 Volumes) written by and published by World Scientific. This book was released on 2020-03-10 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium provides a comprehensive collection of the emergent applications of big data, machine learning, and artificial intelligence technologies to present day physical sciences ranging from materials theory and imaging to predictive synthesis and automated research. This area of research is among the most rapidly developing in the last several years in areas spanning materials science, chemistry, and condensed matter physics.Written by world renowned researchers, the compilation of two authoritative volumes provides a distinct summary of the modern advances in instrument — driven data generation and analytics, establishing the links between the big data and predictive theories, and outlining the emerging field of data and physics-driven predictive and autonomous systems.
Book Synopsis Advanced AI and Internet of Health Things for Combating Pandemics by : Mohamed Lahby
Download or read book Advanced AI and Internet of Health Things for Combating Pandemics written by Mohamed Lahby and published by Springer Nature. This book was released on 2023-07-24 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics.
Book Synopsis Current Applications of Deep Learning in Cancer Diagnostics by : Jyotismita Chaki
Download or read book Current Applications of Deep Learning in Cancer Diagnostics written by Jyotismita Chaki and published by CRC Press. This book was released on 2023-02-22 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques, which are essential to cancer diagnostics. Topics include introduction to current applications of deep learning in cancer diagnostics, pre-processing of cancer data using deep learning, review of deep learning techniques in oncology, overview of advanced deep learning techniques in cancer diagnostics, prediction of cancer susceptibility using deep learning techniques, prediction of cancer reoccurrence using deep learning techniques, deep learning techniques to predict the grading of human cancer, different human cancer detection using deep learning techniques, prediction of cancer survival using deep learning techniques, complexity in the use of deep learning in cancer diagnostics, and challenges and future scopes of deep learning techniques in oncology.
Book Synopsis Ray Tracing: A Tool for All by : Jon Peddie
Download or read book Ray Tracing: A Tool for All written by Jon Peddie and published by Springer. This book was released on 2019-08-08 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to offer a comprehensive overview for anyone wanting to understand the benefits and opportunities of ray tracing, as well as some of the challenges, without having to learn how to program or be an optics scientist. It demystifies ray tracing and brings forward the need and benefit of using ray tracing throughout the development of a film, product, or building — from pitch to prototype to marketing. Ray Tracing and Rendering clarifies the difference between conventional faked rendering and physically correct, photo-realistic ray traced rendering, and explains how programmer’s time, and backend compositing time are saved while producing more accurate representations with 3D models that move. Often considered an esoteric subject the author takes ray tracing out of the confines of the programmer’s lair and shows how all levels of users from concept to construction and sales can benefit without being forced to be a practitioner. It treats both theoretical and practical aspects of the subject as well as giving insights into all the major ray tracing programs and how many of them came about. It will enrich the readers’ understanding of what a difference an accurate high-fidelity image can make to the viewer — our eyes are incredibly sensitive to flaws and distortions and we quickly disregard things that look phony or unreal. Such dismissal by a potential user or customer can spell disaster for a supplier, producer, or developer. If it looks real it will sell, even if it is a fantasy animation. Ray tracing is now within reach of every producer and marketeer, and at prices one can afford, and with production times that meet the demands of today’s fast world.
