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Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. You’ll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you’ll know how to build and deploy production-ready deep learning systems in TensorFlow. Get up and running with TensorFlow, rapidly and painlessly Learn how to use TensorFlow to build deep learning models from the ground up Train popular deep learning models for computer vision and NLP Use extensive abstraction libraries to make development easier and faster Learn how to scale TensorFlow, and use clusters to distribute model training Deploy TensorFlow in a production setting
Satellite images acquired at night provide a visually arresting perspective of the Earth and the human activities that light up the otherwise mostly dark Earth. These night-time light satellite images can be compiled into a geospatial time series that represent an invaluable source of information for both the natural and social sciences. Night-time light remote sensing has been shown to be particularly useful for a range of natural science and social science applications, including studies relating to urban development, demography, sociology, fishing activity, light pollution and the consequences of civil war. Key sensors for these time-series include the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Suomi National Polar-orbiting Partnership Satellite’s Visible Infrared Imaging Radiometer Suite Day/Night Band (Suomi NPP/VIIRS DNB). An increasing number of alternative sources are also available, including high spatial resolution and multispectral sensors. This book captures key methodological issues associated with pre-processing night-time light data, documents state of the art analysis methods, and explores a wide range of applications. Major sections focus on NPP/VIIRS DNB processing; inter-calibration between NPP/VIIRS and DMPS/OLS; applications associated with socio-economic activities, applications in monitoring urbanization; and fishing activity monitoring. The chapters in this book were originally published as a special issue of the International Journal of Remote Sensing.
This publication contains 23 papers on practical and theoretical aspects of calibration and intercalibration of various earth observation satellite sensors, methodology and algorithms, effects of spatial and spectral resolution and early results of RADARSAT.
In our world today, the pervasive threat of air, water, and soil contaminants has reached unprecedented levels, pushing ecosystems to the brink and causing harm to individuals worldwide. Despite numerous attempts by scholars to mitigate this crisis, we find ourselves in the infancy of understanding and combatting these pollutants. The lack of awareness among researchers regarding the types and extent of damage caused by contaminants further exacerbates the problem. This environmental dilemma calls for a transformative solution that not only identifies pollutants but also guides sustainable efforts to cleanse our vital ecosystems. Sensors for Environmental Monitoring, Identification, and Assessment is a groundbreaking book designed to revolutionize environmental research and provide a roadmap for tackling pollution head-on. This comprehensive guide is poised to make a significant impact on scholars, environmentalists, planners, researchers, industrialists, and academics globally. By delving into the diverse realms of environmental sensors, the book equips readers with the knowledge and tools necessary to identify pollutants in varied ecosystems and adopt sustainable approaches for cleanup. Its recommended topics cover critical areas such as indoor pollution, noise pollution, advancements in sensor technology, and the detection of pollutants in soil, water, air, and oceans.
Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book's content intuitive, clearly presented, and practical in its implementation. - Comprehensive overview of various practical methods and algorithms - Detailed description of the principles and procedures of the state-of-the-art algorithms - Real-world case studies open several chapters - More than 500 full-color figures and tables - Edited by top remote sensing experts with contributions from authors across the geosciences
Volume I of the Six Volume Remote Sensing Handbook, Second Edition, is focused on satellites and sensors including radar, light detection and ranging (LiDAR), microwave, hyperspectral, unmanned aerial vehicles (UAVs), and their applications. It discusses data normalization and harmonization, accuracies, and uncertainties of remote sensing products, global navigation satellite system (GNSS) theory and practice, crowdsourcing, cloud computing environments, Google Earth Engine, and remote sensing and space law. This thoroughly revised and updated volume draws on the expertise of a diverse array of leading international authorities in remote sensing and provides an essential resource for researchers at all levels interested in using remote sensing. It integrates discussions of remote sensing principles, data, methods, development, applications, and scientific and social context. FEATURES Provides the most up-to-date comprehensive coverage of remote sensing science. Discusses and analyzes data from old and new generations of satellites and sensors. Provides comprehensive methods and approaches for remote sensing data normalization, standardization, and harmonization. Includes numerous case studies on advances and applications at local, regional, and global scales. Introduces advanced methods in remote sensing such as machine learning, cloud computing, and AI. Highlights scientific achievements over the last decade and provides guidance for future developments. This volume is an excellent resource for the entire remote sensing and GIS community. Academics, researchers, undergraduate and graduate students, as well as practitioners, decision-makers, and policymakers, will benefit from the expertise of the professionals featured in this book, and their extensive knowledge of new and emerging trends.
A volume in the three-volume Remote Sensing Handbook series, Remote Sensing of Water Resources, Disasters, and Urban Studies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Land Reso
Semiannual, with semiannual and annual indexes. References to all scientific and technical literature coming from DOE, its laboratories, energy centers, and contractors. Includes all works deriving from DOE, other related government-sponsored information, and foreign nonnuclear information. Arranged under 39 categories, e.g., Biomedical sciences, basic studies; Biomedical sciences, applied studies; Health and safety; and Fusion energy. Entry gives bibliographical information and abstract. Corporate, author, subject, report number indexes.