Computational Intelligence For Remote Sensing

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Computational Intelligence for Remote Sensing

Manuel Grana,Richard J. Duro
Computational Intelligence for Remote Sensing Book PDF

Author : Manuel Grana,Richard J. Duro
Publisher : Springer Science & Business Media
Page : 397 pages
File Size : 49,8 Mb
Release : 2008-06-05
Category : Computers
ISBN : 9783540793526

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Computational Intelligence for Remote Sensing by Manuel Grana,Richard J. Duro Pdf

This book is a composition of different points of view regarding the application of Computational Intelligence techniques and methods to Remote Sensing data and applications. It is the general consensus that classification, its related data processing, and global optimization methods are core topics of Computational Intelligence. Much of the content of the book is devoted to image segmentation and recognition, using diverse tools from different areas of the Computational Intelligence field, ranging from Artificial Neural Networks to Markov Random Field modeling. The book covers a broad range of topics, starting from the hardware design of hyperspectral sensors, and data handling problems, namely data compression and watermarking issues, as well as autonomous web services. The main contents of the book are devoted to image analysis and efficient (parallel) implementations of these analysis techniques. The classes of images dealt with throughout the book are mostly multispectral-hyperspectral images, though there are some instances of processing Synthetic Aperture Radar images.

Computational Intelligence in Remote Sensing

Yue Wu,Kai Qin,Maoguo Gong
Computational Intelligence in Remote Sensing Book PDF

Author : Yue Wu,Kai Qin,Maoguo Gong
Publisher : Unknown
Page : 0 pages
File Size : 49,8 Mb
Release : 2024-03-15
Category : Technology & Engineering
ISBN : 3725804133

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Computational Intelligence in Remote Sensing by Yue Wu,Kai Qin,Maoguo Gong Pdf

With the advancement of Earth observation techniques, vast amounts of high-resolution remote sensing data are continually captured, proving instrumental in fields such as geography, environmental monitoring, disaster management, and more. However, challenges such as data volume, complex structures, limited labeled samples, and non-convex optimization persist in processing and analyzing remote sensing data. Computational intelligence techniques, inspired by biological intelligence systems, offer potential solutions to these challenges. Computational intelligence (CI) is the theory, design, and application of biologically and linguistically motivated computational paradigms. Traditionally centered around neural networks, fuzzy systems, and evolutionary computation, CI has expanded to include various nature-inspired computing paradigms. These paradigms encompass ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a vital role in developing intelligent systems, including games and cognitive developmental systems. Recent years have seen a surge in deep learning research, with deep convolutional neural networks becoming a core method in artificial intelligence. Many successful AI systems today are based on CI, and it is anticipated that CI will provide effective solutions to challenges in remote sensing in the future.

Computational Intelligence in Remote Sensing

Yue Wu,Kai Qin,Maoguo Gong
Computational Intelligence in Remote Sensing Book PDF

Author : Yue Wu,Kai Qin,Maoguo Gong
Publisher : Unknown
Page : 0 pages
File Size : 54,6 Mb
Release : 2024-03-15
Category : Technology & Engineering
ISBN : 3725804117

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Computational Intelligence in Remote Sensing by Yue Wu,Kai Qin,Maoguo Gong Pdf

With the advancement of Earth observation techniques, vast amounts of high-resolution remote sensing data are continually captured, proving instrumental in fields such as geography, environmental monitoring, disaster management, and more. However, challenges such as data volume, complex structures, limited labeled samples, and non-convex optimization persist in processing and analyzing remote sensing data. Computational intelligence techniques, inspired by biological intelligence systems, offer potential solutions to these challenges. Computational intelligence (CI) is the theory, design, and application of biologically and linguistically motivated computational paradigms. Traditionally centered around neural networks, fuzzy systems, and evolutionary computation, CI has expanded to include various nature-inspired computing paradigms. These paradigms encompass ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a vital role in developing intelligent systems, including games and cognitive developmental systems. Recent years have seen a surge in deep learning research, with deep convolutional neural networks becoming a core method in artificial intelligence. Many successful AI systems today are based on CI, and it is anticipated that CI will provide effective solutions to challenges in remote sensing in the future.

Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation

Maria Pia Del Rosso,Alessandro Sebastianelli,Silvia Liberata Ullo
Artificial Intelligence Applied to Satellite based Remote Sensing Data for Earth Observation Book PDF

Author : Maria Pia Del Rosso,Alessandro Sebastianelli,Silvia Liberata Ullo
Publisher : IET
Page : 283 pages
File Size : 42,8 Mb
Release : 2021-09-14
Category : Computers
ISBN : 9781839532122

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Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation by Maria Pia Del Rosso,Alessandro Sebastianelli,Silvia Liberata Ullo Pdf

This book shows how artificial intelligence, including neural networks and deep learning, can be applied to the processing of satellite data for Earth observation. The authors explain how to develop a set of libraries for the implementation of artificial intelligence that encompass different aspects of research.

Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS

Chang-Wook Lee,Hyangsun Han,Hoonyol Lee
Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS Book PDF

Author : Chang-Wook Lee,Hyangsun Han,Hoonyol Lee
Publisher : Mdpi AG
Page : 166 pages
File Size : 48,9 Mb
Release : 2021-11-11
Category : Science
ISBN : 3036516042

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Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS by Chang-Wook Lee,Hyangsun Han,Hoonyol Lee Pdf

This book is based on Special Issue "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS" from early 2020 to 2021. This book includes seven papers related to the application of artificial intelligence, machine learning and deep learning algorithms using remote sensing and GIS techniques in urban areas.

Computational Intelligence Techniques in Earth and Environmental Sciences

Tanvir Islam,Prashant K. Srivastava,Manika Gupta,Xuan Zhu,Saumitra Mukherjee
Computational Intelligence Techniques in Earth and Environmental Sciences Book PDF

Author : Tanvir Islam,Prashant K. Srivastava,Manika Gupta,Xuan Zhu,Saumitra Mukherjee
Publisher : Springer Science & Business Media
Page : 275 pages
File Size : 44,5 Mb
Release : 2014-02-14
Category : Science
ISBN : 9789401786423

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Computational Intelligence Techniques in Earth and Environmental Sciences by Tanvir Islam,Prashant K. Srivastava,Manika Gupta,Xuan Zhu,Saumitra Mukherjee Pdf

Computational intelligence techniques have enjoyed growing interest in recent decades among the earth and environmental science research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward a sustainable earth. This book compiles a collection of recent developments and rigorous applications of computational intelligence in these disciplines. Techniques covered include artificial neural networks, support vector machines, fuzzy logic, decision-making algorithms, supervised and unsupervised classification algorithms, probabilistic computing, hybrid methods and morphic computing. Further topics given treatment in this volume include remote sensing, meteorology, atmospheric and oceanic modeling, climate change, environmental engineering and management, catastrophic natural hazards, air and environmental pollution and water quality. By linking computational intelligence techniques with earth and environmental science oriented problems, this book promotes synergistic activities among scientists and technicians working in areas such as data mining and machine learning. We believe that a diverse group of academics, scientists, environmentalists, meteorologists and computing experts with a common interest in computational intelligence techniques within the earth and environmental sciences will find this book to be of great value.

Artificial Intelligence Techniques for Satellite Image Analysis

D. Jude Hemanth
Artificial Intelligence Techniques for Satellite Image Analysis Book PDF

Author : D. Jude Hemanth
Publisher : Springer Nature
Page : 274 pages
File Size : 46,9 Mb
Release : 2019-11-13
Category : Computers
ISBN : 9783030241780

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Artificial Intelligence Techniques for Satellite Image Analysis by D. Jude Hemanth Pdf

The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be translated into real-time applications to benefit humankind. Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. It can be also used as a supplementary textbook for graduate students in various engineering branches related to image processing.

Computational Intelligence and Sustainable Systems

H. Anandakumar,R. Arulmurugan,Chow Chee Onn
Computational Intelligence and Sustainable Systems Book PDF

Author : H. Anandakumar,R. Arulmurugan,Chow Chee Onn
Publisher : Springer
Page : 304 pages
File Size : 51,8 Mb
Release : 2018-12-14
Category : Technology & Engineering
ISBN : 9783030026745

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Computational Intelligence and Sustainable Systems by H. Anandakumar,R. Arulmurugan,Chow Chee Onn Pdf

This book features research related to computational intelligence and energy and thermal aware management of computing resources. The authors publish original and timely research in current areas of power, energy, temperature, and environmental engineering as and advances in computational intelligence that are benefiting the fields. Topics include signal processing architectures, algorithms, and applications; biomedical informatics and computation; artificial intelligence and machine learning; green technologies in information; and more. The book includes contributions from a wide range of researchers, academicians, and industry professionals. The book is made up both of extended papers presented at the International Conference on Intelligent Computing and Sustainable System (ICICSS 2018), September 20-21, 2018, and other accepted papers on R&D and original research work related to the practice and theory of technologies to enable and support Intelligent Computing applications.

Computational Intelligence and Intelligent Systems

Zhenhua Li
Computational Intelligence and Intelligent Systems Book PDF

Author : Zhenhua Li
Publisher : Springer Science & Business Media
Page : 496 pages
File Size : 42,9 Mb
Release : 2009-10-05
Category : Computers
ISBN : 9783642049613

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Computational Intelligence and Intelligent Systems by Zhenhua Li Pdf

Volumes CCIS 51 and LNCS 5812 constitute the proceedings of the Fourth Interational Symposium on Intelligence Computation and Applications, ISICA 2009, held in Huangshi, China, during October 23-25. ISICA 2009 attracted over 300 submissions. Through rigorous reviews, 58 papers were included in LNCS 5821,and 54 papers were collected in CCIS 51. ISICA conferences are one of the first series of international conferences on computational intelligence that combine elements of learning, adaptation, evolution and fuzzy logic to create programs as alternative solutions to artificial intelligence.

Deep Learning for the Earth Sciences

Gustau Camps-Valls,Devis Tuia,Xiao Xiang Zhu,Markus Reichstein
Deep Learning for the Earth Sciences Book PDF

Author : Gustau Camps-Valls,Devis Tuia,Xiao Xiang Zhu,Markus Reichstein
Publisher : John Wiley & Sons
Page : 436 pages
File Size : 55,5 Mb
Release : 2021-08-18
Category : Technology & Engineering
ISBN : 9781119646167

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Deep Learning for the Earth Sciences by Gustau Camps-Valls,Devis Tuia,Xiao Xiang Zhu,Markus Reichstein Pdf

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.

Satellite Image Analysis: Clustering and Classification

Surekha Borra,Rohit Thanki,Nilanjan Dey
Satellite Image Analysis Clustering and Classification Book PDF

Author : Surekha Borra,Rohit Thanki,Nilanjan Dey
Publisher : Springer
Page : 97 pages
File Size : 53,8 Mb
Release : 2019-02-08
Category : Technology & Engineering
ISBN : 9789811364242

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Satellite Image Analysis: Clustering and Classification by Surekha Borra,Rohit Thanki,Nilanjan Dey Pdf

Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.

Computational Intelligence Methods for Super-Resolution in Image Processing Applications

Anand Deshpande,Vania V. Estrela,Navid Razmjooy
Computational Intelligence Methods for Super Resolution in Image Processing Applications Book PDF

Author : Anand Deshpande,Vania V. Estrela,Navid Razmjooy
Publisher : Springer Nature
Page : 308 pages
File Size : 51,6 Mb
Release : 2021-05-28
Category : Technology & Engineering
ISBN : 9783030679217

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Computational Intelligence Methods for Super-Resolution in Image Processing Applications by Anand Deshpande,Vania V. Estrela,Navid Razmjooy Pdf

This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.

Remote Sensing Image Processing

Gustavo Camps-Valls
Remote Sensing Image Processing Book PDF

Author : Gustavo Camps-Valls
Publisher : Morgan & Claypool Publishers
Page : 195 pages
File Size : 42,6 Mb
Release : 2011
Category : Computers
ISBN : 9781608458196

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Remote Sensing Image Processing by Gustavo Camps-Valls Pdf

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

Geospatial Intelligence

Fatimazahra Barramou,El Hassan El Brirchi,Khalifa Mansouri,Youness Dehbi
Geospatial Intelligence Book PDF

Author : Fatimazahra Barramou,El Hassan El Brirchi,Khalifa Mansouri,Youness Dehbi
Publisher : Springer Nature
Page : 180 pages
File Size : 41,5 Mb
Release : 2021-11-10
Category : Computers
ISBN : 9783030804589

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Geospatial Intelligence by Fatimazahra Barramou,El Hassan El Brirchi,Khalifa Mansouri,Youness Dehbi Pdf

This book explores cutting-edge methods combining geospatial technologies and artificial intelligence related to several fields such as smart farming, urban planning, geology, transportation, and 3D city models. It introduces techniques which range from machine and deep learning to remote sensing for geospatial data analysis. The book consists of two main parts that include 13 chapters contributed by promising authors. The first part deals with the use of artificial intelligence techniques to improve spatial data analysis, whereas the second part focuses on the use of artificial intelligence with remote sensing in various fields. Throughout the chapters, the interest for the use of artificial intelligence is demonstrated for different geospatial technologies such as aerial imagery, drones, Lidar, satellite remote sensing, and more. The work in this book is dedicated to the scientific community interested in the coupling of geospatial technologies and artificial intelligence and exploring the synergetic effects of both fields. It offers practitioners and researchers from academia, the industry and government information, experiences and research results about all aspects of specialized and interdisciplinary fields on geospatial intelligence.

Advances in Machine Learning and Image Analysis for GeoAI

Saurabh Prasad,Jocelyn Chanussot,Jun Li
Advances in Machine Learning and Image Analysis for GeoAI Book PDF

Author : Saurabh Prasad,Jocelyn Chanussot,Jun Li
Publisher : Elsevier
Page : 366 pages
File Size : 51,5 Mb
Release : 2024-06-01
Category : Science
ISBN : 9780443190780

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Advances in Machine Learning and Image Analysis for GeoAI by Saurabh Prasad,Jocelyn Chanussot,Jun Li Pdf

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