Generative Adversarial Networks For Remote Sensing
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Generative Adversarial Networks For Remote Sensing
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Author : Vibhute, Amol Dattatraya
language : en
Publisher: IGI Global
Release Date : 2025-04-30
Generative Adversarial Networks For Remote Sensing written by Vibhute, Amol Dattatraya and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-30 with Technology & Engineering categories.
Generative adversarial networks (GANs) are transforming the way complex remote sensing data is analyzed, offering innovative solutions for geospatial applications. Traditional methods often struggle to process high-dimensional remotely sensed datasets, leading to limitations in decision-making and predictive accuracy. By leveraging GANs, researchers can enhance feature extraction, object detection, and time-series analysis, enabling more precise environmental monitoring, urban planning, and agricultural assessments. This technological advancement not only improves real-time geospatial analysis but also opens new avenues for interdisciplinary collaboration, ethical considerations, and security challenges in AI-driven remote sensing. As GANs continue to evolve, their application in remote sensing holds the potential to drive sustainability and more informed global decision-making. Generative Adversarial Networks for Remote Sensing emphasizes the foundations of recent trends in GANs and remote sensing applications. It provides insights into the fundamentals of generative adversarial networks, historical advancements, novel GAN architectures and challenges in analyzing remote sensing data using GANs. Covering topics such as change detection, resource management, and feature engineering, this book is an excellent resource for geographers, geospatial data analysts, engineers, professionals, researchers, scholars, academicians, and more.
Artificial Neural Networks And Evolutionary Computation In Remote Sensing
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Author : Taskin Kavzoglu
language : en
Publisher: MDPI
Release Date : 2021-01-19
Artificial Neural Networks And Evolutionary Computation In Remote Sensing written by Taskin Kavzoglu and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-19 with Science categories.
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.
Super Resolution For Remote Sensing Applications Using Deep Learning Techniques
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Author : G. Rohith
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2022-12-14
Super Resolution For Remote Sensing Applications Using Deep Learning Techniques written by G. Rohith and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-14 with Computers categories.
Satellite image processing is crucial in detecting vegetation, clouds, and other atmospheric applications. Due to sensor limitations and pre-processing, remotely sensed satellite images may have interpretability concerns as to specific portions of the image, making it hard to recognise patterns or objects and posing the risk of losing minute details in the image. Existing imaging processors and optical components are expensive to counterfeit, have interpretability issues, and are not necessarily viable in real applications. This book exploits the usage of deep learning (DL) components in feature extraction to boost the minute details of images and their classification implications to tackle such problems. It shows the importance of super-resolution in improving the spatial details of images and aiding digital aerial photography in pan-sharpening, detecting signatures correctly, and making precise decisions with decision-making tools.
Advanced Deep Learning Strategies For The Analysis Of Remote Sensing Images
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Author : Yakoub Bazi
language : en
Publisher: MDPI
Release Date : 2021-06-15
Advanced Deep Learning Strategies For The Analysis Of Remote Sensing Images written by Yakoub Bazi and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Science categories.
The rapid growth of the world population has resulted in an exponential expansion of both urban and agricultural areas. Identifying and managing such earthly changes in an automatic way poses a worth-addressing challenge, in which remote sensing technology can have a fundamental role to answer—at least partially—such demands. The recent advent of cutting-edge processing facilities has fostered the adoption of deep learning architectures owing to their generalization capabilities. In this respect, it seems evident that the pace of deep learning in the remote sensing domain remains somewhat lagging behind that of its computer vision counterpart. This is due to the scarce availability of ground truth information in comparison with other computer vision domains. In this book, we aim at advancing the state of the art in linking deep learning methodologies with remote sensing image processing by collecting 20 contributions from different worldwide scientists and laboratories. The book presents a wide range of methodological advancements in the deep learning field that come with different applications in the remote sensing landscape such as wildfire and postdisaster damage detection, urban forest mapping, vine disease and pavement marking detection, desert road mapping, road and building outline extraction, vehicle and vessel detection, water identification, and text-to-image matching.
Urban Remote Sensing
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Author : Xiaojun X. Yang
language : en
Publisher: John Wiley & Sons
Release Date : 2021-10-06
Urban Remote Sensing written by Xiaojun X. Yang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-06 with Technology & Engineering categories.
Urban Remote Sensing The second edition of Urban Remote Sensing is a state-of-the-art review of the latest progress in the subject. The text examines how evolving innovations in remote sensing allow to deliver the critical information on cities in a timely and cost-effective way to support various urban management activities and the scientific research on urban morphology, socio-environmental dynamics, and sustainability. Chapters are written by leading scholars from a variety of disciplines including remote sensing, GIS, geography, urban planning, environmental science, and sustainability science, with case studies predominately drawn from North America and Europe. A review of the essential and emerging research areas in urban remote sensing including sensors, techniques, and applications, especially some critical issues that are shifting the directions in urban remote sensing research. Illustrated in full color throughout, including numerous relevant case studies and extensive discussions of important concepts and cutting-edge technologies to enable clearer understanding for non-technical audiences. Urban Remote Sensing, Second Edition will be of particular interest to upper-division undergraduate and graduate students, researchers and professionals working in the fields of remote sensing, geospatial information, and urban & environmental planning.
Super Resolution For Remote Sensing
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Author : Michal Kawulok
language : en
Publisher: Springer Nature
Release Date : 2024-10-14
Super Resolution For Remote Sensing written by Michal Kawulok and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Computers categories.
This book provides a comprehensive perspective over the landscape of super-resolution techniques developed for and applied to remotely-sensed images. The chapters tackle the most important problems that professionals face when dealing with super-resolution in the context of remote sensing. These are: evaluation procedures to assess the super-resolution quality; benchmark datasets (simulated and real-life); super-resolution for specific data modalities (e.g., panchromatic, multispectral, and hyperspectral images); single-image super-resolution, including generative adversarial networks; multi-image fusion (temporal and/or spectral); real-world super-resolution; and task-driven super-resolution. The book presents the results of several recent surveys on super-resolution specifically for the remote sensing community.
Classification Methods For Remotely Sensed Data
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Author : Taskin Kavzoglu
language : en
Publisher: CRC Press
Release Date : 2024-09-04
Classification Methods For Remotely Sensed Data written by Taskin Kavzoglu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Technology & Engineering categories.
The third edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data. This book is thoroughly updated to meet the needs of readers today and provides six new chapters on deep learning, feature extraction and selection, multisource image fusion, hyperparameter optimization, accuracy assessment with model explainability, and object-based image analysis, which is relatively a new paradigm in image processing and classification. It presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. New in this edition: Provides comprehensive background on the theory of deep learning and its application to remote sensing data. Includes a chapter on hyperparameter optimization techniques to guarantee the highest performance in classification applications. Outlines the latest strategies and accuracy measures in accuracy assessment and summarizes accuracy metrics and assessment strategies. Discusses the methods used for explaining inherent structures and weighing the features of ML and AI algorithms that are critical for explaining the robustness of the models. This book is intended for industry professionals, researchers, academics, and graduate students who want a thorough and up-to-date guide to the many and varied techniques of image classification applied in the fields of geography, geospatial and earth sciences, electronic and computer science, environmental engineering, etc.
Uav Photogrammetry And Remote Sensing
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Author : Fernando Carvajal-Ramírez
language : en
Publisher: MDPI
Release Date : 2021-09-06
Uav Photogrammetry And Remote Sensing written by Fernando Carvajal-Ramírez and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-06 with Technology & Engineering categories.
The concept of remote sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of Earth observation satellites. The emergence of unmanned aerial vehicles (UAV) with Global Navigation Satellite System (GNSS) controlled navigation and sensor-carrying capabilities has increased the number of publications related to new remote sensing from much closer distances. Previous knowledge about the behavior of the Earth's surface under the incidence different wavelengths of energy has been successfully applied to a large amount of data recorded from UAVs, thereby increasing the special and temporal resolution of the products obtained. More specifically, the ability of UAVs to be positioned in the air at pre-programmed coordinate points; to track flight paths; and in any case, to record the coordinates of the sensor position at the time of the shot and at the pitch, yaw, and roll angles have opened an interesting field of applications for low-altitude aerial photogrammetry, known as UAV photogrammetry. In addition, photogrammetric data processing has been improved thanks to the combination of new algorithms, e.g., structure from motion (SfM), which solves the collinearity equations without the need for any control point, producing a cloud of points referenced to an arbitrary coordinate system and a full camera calibration, and the multi-view stereopsis (MVS) algorithm, which applies an expanding procedure of sparse set of matched keypoints in order to obtain a dense point cloud. The set of technical advances described above allows for geometric modeling of terrain surfaces with high accuracy, minimizing the need for topographic campaigns for georeferencing of such products. This Special Issue aims to compile some applications realized thanks to the synergies established between new remote sensing from close distances and UAV photogrammetry.
Enhancing Security In Public Spaces Through Generative Adversarial Networks Gans
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Author : Ponnusamy, Sivaram
language : en
Publisher: IGI Global
Release Date : 2024-05-16
Enhancing Security In Public Spaces Through Generative Adversarial Networks Gans written by Ponnusamy, Sivaram and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-16 with Computers categories.
As the demand for data security intensifies, the vulnerabilities become glaring, exposing sensitive information to potential threats. In this tumultuous landscape, Generative Adversarial Networks (GANs) emerge as a groundbreaking solution, transcending their initial role as image generators to become indispensable guardians of data security. Within the pages of Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs), readers are guided through the intricate world of GANs, unraveling their unique design and dynamic adversarial training. The book presents GANs not merely as a technical marvel but as a strategic asset for organizations, offering a comprehensive solution to fortify cybersecurity, protect data privacy, and mitigate the risks associated with evolving cyber threats. It navigates the ethical considerations surrounding GANs, emphasizing the delicate balance between technological advancement and responsible use.
Crafting Images With Generative Adversarial Networks Gans And Models
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Author : Dubey, Parul
language : en
Publisher: IGI Global
Release Date : 2025-03-13
Crafting Images With Generative Adversarial Networks Gans And Models written by Dubey, Parul and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Computers categories.
Generative Adversarial Networks (GANs) are transforming the field of artificial intelligence by enabling the creation of highly realistic images, pushing the boundaries of creativity and automation. These models have vast applications, from art and design to medical imaging and data augmentation, offering new possibilities across industries. Understanding GANs is essential for harnessing their potential while addressing challenges like ethical considerations and model biases. As AI-generated content becomes more prevalent, mastering these technologies will be crucial for researchers, developers, and creatives shaping the future of digital innovation. Crafting Images With Generative Adversarial Networks (GANs) and Models demystifies the complexities of GANs and provides a solid foundation for understanding and leveraging these powerful generative models. It also explores real-world applications of GANs across diverse domains, including art generation, image editing, and content creation. Covering topics such as photorealism, text-to-image, and attention mechanisms, this book is an excellent resource for data scientists, computer vision researchers, AI engineers, graphic designers, media professionals, industry practitioners, professionals, researchers, scholars, academicians, and more.