Multisensor Data Fusion And Machine Learning For Environmental Remote Sensing

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Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Author : Ni-Bin Chang
Publisher : CRC Press
ISBN 13 : 1498774342
Total Pages : 508 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing by : Ni-Bin Chang

Download or read book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing written by Ni-Bin Chang and published by CRC Press. This book was released on 2018-02-21 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.

Multisensor Data Fusion

Author : David Hall
Publisher : CRC Press
ISBN 13 : 1420038540
Total Pages : 564 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Multisensor Data Fusion by : David Hall

Download or read book Multisensor Data Fusion written by David Hall and published by CRC Press. This book was released on 2001-06-20 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut

Multisensor Fusion

Author : Anthony K. Hyder
Publisher : Springer Science & Business Media
ISBN 13 : 9401005567
Total Pages : 929 pages
Book Rating : 4.4/5 (1 download)

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Book Synopsis Multisensor Fusion by : Anthony K. Hyder

Download or read book Multisensor Fusion written by Anthony K. Hyder and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: For some time, all branches of the military have used a wide range of sensors to provide data for many purposes, including surveillance, reconnoitring, target detection and battle damage assessment. Many nations have also attempted to utilise these sensors for civilian applications, such as crop monitoring, agricultural disease tracking, environmental diagnostics, cartography, ocean temperature profiling, urban planning, and the characterisation of the Ozone Hole above Antarctica. The recent convergence of several important technologies has made possible new, advanced, high performance, sensor based applications relying on the near-simultaneous fusion of data from an ensemble of different types of sensors. The book examines the underlying principles of sensor operation and data fusion, the techniques and technologies that enable the process, including the operation of 'fusion engines'. Fundamental theory and the enabling technologies of data fusion are presented in a systematic and accessible manner. Applications are discussed in the areas of medicine, meteorology, BDA and targeting, transportation, cartography, the environment, agriculture, and manufacturing and process control.

Multi-Sensor Systems and Data Fusion in Remote Sensing

Author : Piotr Kaniewski
Publisher : Mdpi AG
ISBN 13 : 9783036567983
Total Pages : 0 pages
Book Rating : 4.5/5 (679 download)

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Book Synopsis Multi-Sensor Systems and Data Fusion in Remote Sensing by : Piotr Kaniewski

Download or read book Multi-Sensor Systems and Data Fusion in Remote Sensing written by Piotr Kaniewski and published by Mdpi AG. This book was released on 2023-03-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing is developing rapidly due to progress in many interconnected fields. It includes the emergence of new sensors, development of sophisticated platforms for those sensors, and advances in signal and data processing. The progress in the fields of radar, optoelectronic, acoustic, magnetic, chemical, and other sensors is stunning. Whereas the mentioned sensors are currently more sensitive and accurate, have improved resolutions, data rates, and dynamical ranges, they still have their limitations. The utilization of multi-sensor systems and joint processing of their signals or data has long been considered an effective solution for reducing the disadvantages and best utilizing their strengths. The emergence of new types of sensors creates an opportunity for scientists and engineers to develop new and more capable integrated multi-sensor systems. It is necessary to mention that the users' expectations with respect to the size of the observed area or volume, data resolution, accuracy, speed of operation, and functionality of remote sensing systems are still increasing. Extended frequency bands, improved resolutions, and data rates of the new sensors as well as the common use of distributed sensors increase the influx of data in contemporary multi-sensor systems. These facts pose new challenges for the data fusion algorithms that must often employ the newest achievements from the areas of big data mining, statistical estimation, artificial intelligence, etc. This book contains a collection of papers that provide a fresh insight into the newest developments in the fields of multi-sensor systems and data fusion.

Optical Remote Sensing of Ocean Hydrodynamics

Author : Victor Raizer
Publisher : CRC Press
ISBN 13 : 1351119176
Total Pages : 280 pages
Book Rating : 4.3/5 (511 download)

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Book Synopsis Optical Remote Sensing of Ocean Hydrodynamics by : Victor Raizer

Download or read book Optical Remote Sensing of Ocean Hydrodynamics written by Victor Raizer and published by CRC Press. This book was released on 2019-03-04 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optical Remote Sensing is one of the main technologies used in sea surface monitoring. Optical Remote Sensing of Ocean Hydrodynamics investigates and demonstrates capabilities of optical remote sensing technology for enhanced observations and detection of ocean environments. It provides extensive knowledge of physical principles and capabilities of optical observations of the oceans at high spatial resolution, 1-4m, and on the observations of surface wave hydrodynamic processes. It also describes the implementation of spectral-statistical and fusion algorithms for analyses of multispectral optical databases and establishes physics-based criteria for detection of complex wave phenomena and hydrodynamic disturbances including assessment and management of optical databases. This book explains the physical principles of high-resolution optical imagery of the ocean surface, discusses for the first time the capabilities of observing hydrodynamic processes and events, and emphasizes the integration of optical measurements and enhanced data analysis. It also covers both the assessment and the interpretation of dynamic multispectral optical databases and includes applications for advanced studies and nonacoustic detection. This book is an invaluable resource for researches, industry professionals, engineers, and students working on cross-disciplinary problems in ocean hydrodynamics, optical remote sensing of the ocean and sea surface remote sensing. Readers in the fields of geosciences and remote sensing, applied physics, oceanography, satellite observation technology, and optical engineering will learn the theory and practice of optical interactions with the ocean.

Multi-Sensor and Multi-Temporal Remote Sensing

Author : Anil Kumar
Publisher : CRC Press
ISBN 13 : 100087219X
Total Pages : 178 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Multi-Sensor and Multi-Temporal Remote Sensing by : Anil Kumar

Download or read book Multi-Sensor and Multi-Temporal Remote Sensing written by Anil Kumar and published by CRC Press. This book was released on 2023-04-17 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the ‘individual sample as mean’ training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields. Key features: Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classes Discusses range of fuzzy/deep learning models capable to extract specific single class and separates noise Describes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a class Supports multi-sensor and multi-temporal data processing through in-house SMIC software Includes case studies and practical applications for single class mapping This book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas.

Intelligent Data Mining and Fusion Systems in Agriculture

Author : Xanthoula Eirini Pantazi
Publisher : Academic Press
ISBN 13 : 0128143924
Total Pages : 330 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Intelligent Data Mining and Fusion Systems in Agriculture by : Xanthoula Eirini Pantazi

Download or read book Intelligent Data Mining and Fusion Systems in Agriculture written by Xanthoula Eirini Pantazi and published by Academic Press. This book was released on 2019-10-08 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agriculture Addresses AI use in weed management, disease detection, yield prediction and crop production Utilizes case studies to provide real-world insights and direction

Multi-sensor System Applications in the Everglades Ecosystem

Author : Caiyun Zhang
Publisher : CRC Press
ISBN 13 : 0429530781
Total Pages : 409 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Multi-sensor System Applications in the Everglades Ecosystem by : Caiyun Zhang

Download or read book Multi-sensor System Applications in the Everglades Ecosystem written by Caiyun Zhang and published by CRC Press. This book was released on 2020-01-06 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the applicability of multiple remote sensors to acquire information relevant to restoration and conservation efforts in wetlands using data collected from airborne and space multispectral/hyperspectral sensors, light detection and ranging (LiDAR), Unmanned Aircraft Systems (UAS), and a hand-held spectroradiometer. This book also examines digital data processing techniques such as object-based image analysis, machine learning, texture analysis, and data fusion. After an introduction to the Everglades and to remote sensing, the book is divided into four parts based on the sensor systems used. There are chapters on vegetation mapping, biomass and water quality modeling, applications of hyperspectral data for plant stress analysis and coral reef mapping, studies of airborne LiDAR data for coastal vulnerability analysis and DEM improvement, as well as chapters that explore a fusion of multiple sensors for different datasets. Features Introduces concepts, theories, and advanced processing techniques A complete introduction of machine learning, object-based image analysis, data fusion, and ensemble analysis techniques in processing data from multiple remote sensors Explains how multiple remote sensing systems are applied in the wetland ecosystems of Florida The author had been teaching and using both systems and her research is widely recognized Multi-sensor System Applications in the Everglades Ecosystems provides a comprehensive application of remote sensing techniques in the Florida Everglades and its coastal ecosystems. It will prove an invaluable resource for the restoration and conservation of the Florida Everglades and beyond, for global wetlands in general. Any professional, scientist, engineer, or student working with remote sensing and wetland ecosystems will reap enormous benefits from this book.

Image Fusion in Remote Sensing

Author : Arian Azarang
Publisher : Springer Nature
ISBN 13 : 3031022564
Total Pages : 89 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Image Fusion in Remote Sensing by : Arian Azarang

Download or read book Image Fusion in Remote Sensing written by Arian Azarang and published by Springer Nature. This book was released on 2022-05-31 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image fusion in remote sensing or pansharpening involves fusing spatial (panchromatic) and spectral (multispectral) images that are captured by different sensors on satellites. This book addresses image fusion approaches for remote sensing applications. Both conventional and deep learning approaches are covered. First, the conventional approaches to image fusion in remote sensing are discussed. These approaches include component substitution, multi-resolution, and model-based algorithms. Then, the recently developed deep learning approaches involving single-objective and multi-objective loss functions are discussed. Experimental results are provided comparing conventional and deep learning approaches in terms of both low-resolution and full-resolution objective metrics that are commonly used in remote sensing. The book is concluded by stating anticipated future trends in pansharpening or image fusion in remote sensing.

Body Sensor Networks

Author : Guang-Zhong Yang
Publisher : Springer
ISBN 13 : 1447163745
Total Pages : 564 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Body Sensor Networks by : Guang-Zhong Yang

Download or read book Body Sensor Networks written by Guang-Zhong Yang and published by Springer. This book was released on 2014-04-16 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vivo monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing. In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering. Biosensor Design, Interfacing and Nanotechnology Wireless Communication and Network Topologies Communication Protocols and Standards Energy Harvesting and Power Delivery Ultra-low Power Bio-inspired Processing Multi-sensor Fusion and Context Aware Sensing Autonomic Sensing Wearable, Ingestible Sensor Integration and Exemplar Applications System Integration and Wireless Sensor Microsystems The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of the BSN development kit.

Remote Sensing Image Processing

Author : Gustavo Camps-Valls
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1608458202
Total Pages : 194 pages
Book Rating : 4.6/5 (84 download)

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Book Synopsis Remote Sensing Image Processing by : Gustavo Camps-Valls

Download or read book Remote Sensing Image Processing written by Gustavo Camps-Valls and published by Morgan & Claypool Publishers. This book was released on 2011-12-11 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earth observation is the field of science concerned with the problem of monitoring and modeling the processes on the Earth surface and their interaction with the atmosphere. The Earth is continuously monitored with advanced optical and radar sensors. The images are analyzed and processed to deliver useful products to individual users, agencies and public administrations. To deal with these problems, remote sensing image processing is nowadays a mature research area, and the techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, data coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This book covers some of the fields in a comprehensive way. Table of Contents: Remote Sensing from Earth Observation Satellites / The Statistics of Remote Sensing Images / Remote Sensing Feature Selection and Extraction / Classification / Spectral Mixture Analysis / Estimation of Physical Parameters

Advances in Remote Sensing for Forest Monitoring

Author : Prem C. Pandey
Publisher : John Wiley & Sons
ISBN 13 : 1119788129
Total Pages : 405 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Advances in Remote Sensing for Forest Monitoring by : Prem C. Pandey

Download or read book Advances in Remote Sensing for Forest Monitoring written by Prem C. Pandey and published by John Wiley & Sons. This book was released on 2022-10-11 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Remote Sensing for Forest Monitoring An expert overview of remote sensing as applied to forests and other vegetation In Advances in Remote Sensing for Forest Monitoring, a team of distinguished researchers delivers an expansive and insightful discussion of the latest research on remote sensing technologies as they relate to the monitoring of forests, plantations, and other vegetation. The authors also explore the use of unmanned aerial vehicles and drones, as well as multisource and multi-sensor data – such as optical, SAR, LIDAR, and hyperspectral data. The book draws on the latest data and research to show how remote sensing solutions are being used in real-world settings. It offers contributions from researchers and practitioners from a wide variety of backgrounds and geographical regions to provide a diverse and global set of perspectives on the subject. Readers will also find: A thorough introduction to forest monitoring using remote sensing including recent advances in remote sensing technology Comprehensive explorations of sustainable forest management to enhance ecosystem services and livelihood security using a geospatial approach Case studies of monitoring the biochemical and biophysical parameters of forests, including carotene and xanthophyll content Practical advice on how to apply machine learning tools to remote sensing data Perfect for postgraduates, lecturers, and researchers in the fields of environmental science, forestry, and natural resource management, Advances in Remote Sensing for Forest Monitoring will also earn a place in the libraries of professionals and researchers working with remote sensing technology.

Advances in Environmental Remote Sensing

Author : Qihao Weng
Publisher : CRC Press
ISBN 13 : 1420091816
Total Pages : 610 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Advances in Environmental Remote Sensing by : Qihao Weng

Download or read book Advances in Environmental Remote Sensing written by Qihao Weng and published by CRC Press. This book was released on 2011-02-16 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generating a satisfactory classification image from remote sensing data is not a straightforward task. Many factors contribute to this difficulty including the characteristics of a study area, availability of suitable remote sensing data, ancillary and ground reference data, proper use of variables and classification algorithms, and the analyst's e

Computer Processing of Remotely-Sensed Images

Author : Paul M. Mather
Publisher : John Wiley & Sons
ISBN 13 : 1119502829
Total Pages : 388 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Computer Processing of Remotely-Sensed Images by : Paul M. Mather

Download or read book Computer Processing of Remotely-Sensed Images written by Paul M. Mather and published by John Wiley & Sons. This book was released on 2022-04-11 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer Processing of Remotely-Sensed Images A thorough introduction to computer processing of remotely-sensed images, processing methods, and applications Remote sensing is a crucial form of measurement that allows for the gauging of an object or space without direct physical contact, allowing for the assessment and recording of a target under conditions which would normally render access difficult or impossible. This is done through the analysis and interpretation of electromagnetic radiation (EMR) that is reflected or emitted by an object, surveyed and recorded by an observer or instrument that is not in contact with the target. This methodology is particularly of importance in Earth observation by remote sensing, wherein airborne or satellite-borne instruments of EMR provide data on the planet’s land, seas, ice, and atmosphere. This permits scientists to establish relationships between the measurements and the nature and distribution of phenomena on the Earth’s surface or within the atmosphere. Still relying on a visual and conceptual approach to the material, the fifth edition of this successful textbook provides students with methods of computer processing of remotely sensed data and introduces them to environmental applications which make use of remotely-sensed images. The new edition’s content has been rearranged to be more clearly focused on image processing methods and applications in remote sensing with new examples, including material on the Copernicus missions, microsatellites and recently launched SAR satellites, as well as time series analysis methods. The fifth edition of Computer Processing of Remotely-Sensed Images also contains: A cohesive presentation of the fundamental components of Earth observation remote sensing that is easy to understand and highly digestible Largely non-technical language providing insights into more advanced topics that may be too difficult for a non-mathematician to understand Illustrations and example boxes throughout the book to illustrate concepts, as well as revised examples that reflect the latest information References and links to the most up-to-date online and open access sources used by students Computer Processing of Remotely-Sensed Images is a highly insightful textbook for advanced undergraduates and postgraduate students taking courses in remote sensing and GIS in Geography, Geology, and Earth & Environmental Science departments.

Springer Handbook of Robotics

Author : Bruno Siciliano
Publisher : Springer
ISBN 13 : 3319325523
Total Pages : 2259 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Springer Handbook of Robotics by : Bruno Siciliano

Download or read book Springer Handbook of Robotics written by Bruno Siciliano and published by Springer. This book was released on 2016-07-27 with total page 2259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this handbook provides a state-of-the-art overview on the various aspects in the rapidly developing field of robotics. Reaching for the human frontier, robotics is vigorously engaged in the growing challenges of new emerging domains. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The credible prospect of practical robots among humans is the result of the scientific endeavour of a half a century of robotic developments that established robotics as a modern scientific discipline. The ongoing vibrant expansion and strong growth of the field during the last decade has fueled this second edition of the Springer Handbook of Robotics. The first edition of the handbook soon became a landmark in robotics publishing and won the American Association of Publishers PROSE Award for Excellence in Physical Sciences & Mathematics as well as the organization’s Award for Engineering & Technology. The second edition of the handbook, edited by two internationally renowned scientists with the support of an outstanding team of seven part editors and more than 200 authors, continues to be an authoritative reference for robotics researchers, newcomers to the field, and scholars from related disciplines. The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications. Further to an extensive update, fifteen new chapters have been introduced on emerging topics, and a new generation of authors have joined the handbook’s team. A novel addition to the second edition is a comprehensive collection of multimedia references to more than 700 videos, which bring valuable insight into the contents. The videos can be viewed directly augmented into the text with a smartphone or tablet using a unique and specially designed app. Springer Handbook of Robotics Multimedia Extension Portal: http://handbookofrobotics.org/

Learning to Understand Remote Sensing Images

Author : Qi Wang
Publisher : MDPI
ISBN 13 : 3038976989
Total Pages : 376 pages
Book Rating : 4.0/5 (389 download)

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Book Synopsis Learning to Understand Remote Sensing Images by : Qi Wang

Download or read book Learning to Understand Remote Sensing Images written by Qi Wang and published by MDPI. This book was released on 2019-09-30 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.

Advances in Machine Learning and Image Analysis for GeoAI

Author : Saurabh Prasad
Publisher : Elsevier
ISBN 13 : 044319078X
Total Pages : 366 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Advances in Machine Learning and Image Analysis for GeoAI by : Saurabh Prasad

Download or read book Advances in Machine Learning and Image Analysis for GeoAI written by Saurabh Prasad and published by Elsevier. This book was released on 2024-06-01 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Machine Learning and Image Analysis for GeoAI provides state-of-the-art machine learning and signal processing techniques for a comprehensive collection of geospatial sensors and sensing platforms. The book covers supervised, semi-supervised and unsupervised geospatial image analysis, sensor fusion across modalities, image super-resolution, transfer learning across sensors and time-points, and spectral unmixing among other topics. The chapters in these thematic areas cover a variety of algorithmic frameworks such as variants of convolutional neural networks, graph convolutional networks, multi-stream networks, Bayesian networks, generative adversarial networks, transformers and more.Advances in Machine Learning and Image Analysis for GeoAI provides graduate students, researchers and practitioners in the area of signal processing and geospatial image analysis with the latest techniques to implement deep learning strategies in their research. Covers the latest machine learning and signal processing techniques that can effectively leverage geospatial imagery at scale Presents a variety of algorithmic frameworks, including variants of convolutional neural networks, multi-stream networks, Bayesian networks, and more Includes open-source code-base for algorithms described in each chapter