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Evolutionary Computation For Information Extraction From Remotely Sensed Imagery
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Book Synopsis Evolutionary Computation for Information Extraction from Remotely Sensed Imagery by : Henrique Garcia Momm
Download or read book Evolutionary Computation for Information Extraction from Remotely Sensed Imagery written by Henrique Garcia Momm and published by . This book was released on 2008 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Automated and semi-automated techniques have been researched as an alternative way to reduce human interaction and thus improve the information extraction process from imagery. This research developed an innovative methodology by integrating machine learning algorithms with image processing and remote sensing procedures to form the evolutionary framework . In this biologically-inspired methodology, non-linear solutions are developed by iteratively updating a set of candidate solutions through operations such as: reproduction, competition, and selection. Uncertainty analysis is conducted to quantitatively assess the system's variability due to the random generation of the initial set of candidate solutions, from which the algorithm begins. A new convergence approach is proposed and results indicate that it not only reduces the overall variability of the system but also the number of iterations needed to obtain the optimal solution. Additionally, the evolutionary framework is evaluated in solving different remote sensing problems, such as: non-linear inverse modeling, integration of image texture with spectral information, and multitemporal feature extraction. The investigations in this research revealed that the use of evolutionary computation to solve remote sensing problems is feasible. Results also indicate that, the evolutionary framework reduces the overall dimensionality of the data by removing redundant information while generating robust solutions regardless of the variations in the statistics and the distribution of the data. Thus, signifying that the proposed framework is capable of mathematically incorporating the non-linear relationship between features into the final solution.
Book Synopsis Artificial Neural Networks and Evolutionary Computation in Remote Sensing by : Taskin Kavzoglu
Download or read book Artificial Neural Networks and Evolutionary Computation in Remote Sensing written by Taskin Kavzoglu and published by MDPI. This book was released on 2021-01-19 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
Book Synopsis Feature Extraction from High-Resolution Remotely Sensed Imagery Using Evolutionary Computation by : Henrique Momm
Download or read book Feature Extraction from High-Resolution Remotely Sensed Imagery Using Evolutionary Computation written by Henrique Momm and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Artificial Neural Networks and Evolutionary Computation in Remote Sensing by : Taskin Kavzoglu
Download or read book Artificial Neural Networks and Evolutionary Computation in Remote Sensing written by Taskin Kavzoglu and published by . This book was released on 2021 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
Book Synopsis Development and Evaluation of Algorithms and Methodologies of an Automated Spatial Change Information Extraction System from Remotely Sensed Imagery by : Xiaolong Dai
Download or read book Development and Evaluation of Algorithms and Methodologies of an Automated Spatial Change Information Extraction System from Remotely Sensed Imagery written by Xiaolong Dai and published by . This book was released on 1997 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 627 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.
Book Synopsis Advances in Computation and Intelligence by : Sanyou Zeng
Download or read book Advances in Computation and Intelligence written by Sanyou Zeng and published by Springer. This book was released on 2007-08-26 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Symposium on Intelligence Computation and Applications, ISICA 2007, held in Wuhan, China, in September 2007. The 71 revised full papers cover such topics as evolutionary computation, evolutionary learning, neural networks, swarms, pattern recognition, and data mining.
Book Synopsis Advanced Remote Sensing by : Shunlin Liang
Download or read book Advanced Remote Sensing written by Shunlin Liang and published by Academic Press. This book was released on 2012-08-17 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Information Processing for Remote Sensing by : Chi-hau Chen
Download or read book Information Processing for Remote Sensing written by Chi-hau Chen and published by World Scientific. This book was released on 1999 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most comprehensive study of information processing techniques and issues in remote sensing. Topics covered include image and signal processing, pattern recognition and feature extraction for remote sensing, neural networks and wavelet transforms in remote sensing, remote sensing of ocean and coastal environment, SAR image filtering and segmentation, knowledge-based systems, software and hardware issues, data compression, change detection, etc. Emphasis is placed on environmental issues of remote sensing.With 58 color illustrations.
Book Synopsis Differential Evolution by : Anyong Qing
Download or read book Differential Evolution written by Anyong Qing and published by John Wiley & Sons. This book was released on 2009-07-23 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Differential evolution is a very simple but very powerful stochastic optimizer. Since its inception, it has proved very efficient and robust in function optimization and has been applied to solve problems in many scientific and engineering fields. In Differential Evolution , Dr. Qing begins with an overview of optimization, followed by a state-of-the-art review of differential evolution, including its fundamentals and up-to-date advances. He goes on to explore the relationship between differential evolution strategies, intrinsic control parameters, non-intrinsic control parameters, and problem features through a parametric study. Findings and recommendations on the selection of strategies and intrinsic control parameter values are presented. Lastly, after an introductory review of reported applications in electrical and electronic engineering fields, different research groups demonstrate how the methods can be applied to such areas as: multicast routing, multisite mapping in grid environments, antenna arrays, analog electric circuit sizing, electricity markets, stochastic tracking in video sequences, and color quantization. Contains a systematic and comprehensive overview of differential evolution Reviews the latest differential evolution research Describes a comprehensive parametric study conducted over a large test bed Shows how methods can be practically applied to mobile communications grid computing circuits image processing power engineering Sample applications demonstrated by research groups in the United Kingdom, Australia, Italy, Turkey, China, and Eastern Europe Provides access to companion website with code examples for download Differential Evolution is ideal for application engineers, who can use the methods described to solve specific engineering problems. It is also a valuable reference for post-graduates and researchers working in evolutionary computation, design optimization and artificial intelligence. Researchers in the optimization field or engineers and managers involved in operations research will also find the book a helpful introduction to the topic.
Book Synopsis Kansei Engineering and Soft Computing: Theory and Practice by : Dai, Ying
Download or read book Kansei Engineering and Soft Computing: Theory and Practice written by Dai, Ying and published by IGI Global. This book was released on 2010-08-31 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kansei Engineering and Soft Computing: Theory and Practice offers readers a comprehensive review of kansei engineering, soft computing techniques, and the fusion of these two fields from a variety of viewpoints. It explores traditional technologies, as well as solutions to real-world problems through the concept of kansei and the effective utilization of soft computing techniques. This publication is an essential read for professionals, researchers, and students in the field of kansei information processing and soft computing providing both theoretical and practical viewpoints of research in humanized technology.
Book Synopsis Remote Sensing for Environmental Monitoring by : Samy Ismail Elmahdy
Download or read book Remote Sensing for Environmental Monitoring written by Samy Ismail Elmahdy and published by Frontiers Media SA. This book was released on 2024-02-14 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in object-based image analysis, commercial high-resolution satellite sensors, and unmanned aerial vehicles, there is growing interest in studying terrestrial, pollution, catastrophe, and ocean dynamics using a range of high-resolution remote sensing data (UAV). High and extremely high-resolution optical and microwave images enable the extraction of more information from a variety of resource management domains, including agriculture, forestry, geological resources, water resources, cryosphere, atmosphere, and analytics for climate change. Researchers have started utilizing advanced techniques for fine-level information extraction, new sensors and platforms, improved quantification, and characterization of physical environments, patterns, and processes. High-quality articles addressing the use and application of remote sensing in environmental studies will be published in this Research Topic.
Book Synopsis Laser Scanning Systems in Highway and Safety Assessment by : Biswajeet Pradhan
Download or read book Laser Scanning Systems in Highway and Safety Assessment written by Biswajeet Pradhan and published by Springer. This book was released on 2019-04-02 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to promote the core understanding of a proper modelling of road traffic accidents by deep learning methods using traffic information and road geometry delineated from laser scanning data. The first two chapters of the book introduce the reader to laser scanning technology with creative explanation and graphical illustrations, review and recent methods of extracting geometric road parameters. The next three chapters present different machine learning and statistical techniques applied to extract road geometry information from laser scanning data. Chapters 6 and 7 present methods for modelling roadside features and automatic road geometry identification in vector data. After that, this book goes on reviewing methods used for road traffic accident modelling including accident frequency and injury severity of the traffic accident (Chapter 8). Then, the next chapter explores the details of neural networks and their performance in predicting the traffic accidents along with a comparison with common data mining models. Chapter 10 presents a novel hybrid model combining extreme gradient boosting and deep neural networks for predicting injury severity of road traffic accidents. This chapter is followed by deep learning applications in modelling accident data using feed-forward, convolutional, recurrent neural network models (Chapter 11). The final chapter (Chapter 12) presents a procedure for modelling traffic accident with little data based on the concept of transfer learning. This book aims to help graduate students, professionals, decision makers, and road planners in developing better traffic accident prediction models using advanced neural networks.
Book Synopsis Remote Sensing for Target Object Detection and Identification by : Gemine Vivone
Download or read book Remote Sensing for Target Object Detection and Identification written by Gemine Vivone and published by MDPI. This book was released on 2020-03-06 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amount of data acquired by sensors mounted on satellite, airborne, and unmanned aerial vehicle (UAV) platforms. This book promotes papers exploiting different remote sensing data for target object detection and identification, such as synthetic aperture radar (SAR) imaging and multispectral and hyperspectral imaging. Several cutting-edge contributions, which provide examples of how to select of a technology or another depending on the specific application, will be detailed.
Book Synopsis Genetic and Evolutionary Computation Conference by :
Download or read book Genetic and Evolutionary Computation Conference written by and published by . This book was released on 2005 with total page 1164 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Intelligence Computation and Evolutionary Computation by : Zhenyu Du
Download or read book Intelligence Computation and Evolutionary Computation written by Zhenyu Du and published by Springer Science & Business Media. This book was released on 2012-08-13 with total page 1040 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2012 International Conference of Intelligence Computation and Evolutionary Computation (ICEC 2012) is held on July 7, 2012 in Wuhan, China. This conference is sponsored by Information Technology & Industrial Engineering Research Center. ICEC 2012 is a forum for presentation of new research results of intelligent computation and evolutionary computation. Cross-fertilization of intelligent computation, evolutionary computation, evolvable hardware and newly emerging technologies is strongly encouraged. The forum aims to bring together researchers, developers, and users from around the world in both industry and academia for sharing state-of-art results, for exploring new areas of research and development, and to discuss emerging issues facing intelligent computation and evolutionary computation.
Book Synopsis Remote Sensing Imagery by : Florence Tupin
Download or read book Remote Sensing Imagery written by Florence Tupin and published by John Wiley & Sons. This book was released on 2014-02-19 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.
