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Computational Intelligence for Remote Sensing

Computational Intelligence for Remote Sensing PDF Author: Manuel Grana
Publisher: Springer Science & Business Media
ISBN: 3540793526
Category : Computers
Languages : en
Pages : 397

Book Description
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 for Remote Sensing

Computational Intelligence for Remote Sensing PDF Author: Manuel Grana
Publisher: Springer Science & Business Media
ISBN: 3540793526
Category : Computers
Languages : en
Pages : 397

Book Description
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.

Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS

Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS PDF Author: Chang-Wook Lee
Publisher: Mdpi AG
ISBN: 9783036516042
Category : Science
Languages : en
Pages : 166

Book Description
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 in Remote Sensing

Computational Intelligence in Remote Sensing PDF Author: Yue Wu
Publisher:
ISBN: 9783725804139
Category : Technology & Engineering
Languages : en
Pages : 0

Book Description
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

Computational Intelligence in Remote Sensing PDF Author: Yue Wu
Publisher:
ISBN: 9783725804115
Category : Technology & Engineering
Languages : en
Pages : 0

Book Description
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 and Intelligent Systems

Computational Intelligence and Intelligent Systems PDF Author: Zhenhua Li
Publisher: Springer Science & Business Media
ISBN: 3642049613
Category : Computers
Languages : en
Pages : 496

Book Description
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.

Computational Intelligence for Pattern Recognition

Computational Intelligence for Pattern Recognition PDF Author: Witold Pedrycz
Publisher: Springer
ISBN: 3319896296
Category : Technology & Engineering
Languages : en
Pages : 428

Book Description
The book presents a comprehensive and up-to-date review of fuzzy pattern recognition. It carefully discusses a range of methodological and algorithmic issues, as well as implementations and case studies, and identifies the best design practices, assesses business models and practices of pattern recognition in real-world applications in industry, health care, administration, and business. Since the inception of fuzzy sets, fuzzy pattern recognition with its methodology, algorithms, and applications, has offered new insights into the principles and practice of pattern classification. Computational intelligence (CI) establishes a comprehensive framework aimed at fostering the paradigm of pattern recognition. The collection of contributions included in this book offers a representative overview of the advances in the area, with timely, in-depth and comprehensive material on the conceptually appealing and practically sound methodology and practices of CI-based pattern recognition.

Artificial Intelligence Techniques for Satellite Image Analysis

Artificial Intelligence Techniques for Satellite Image Analysis PDF Author: D. Jude Hemanth
Publisher: Springer Nature
ISBN: 3030241785
Category : Computers
Languages : en
Pages : 274

Book Description
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.

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

Artificial Intelligence Applied to Satellite-based Remote Sensing Data for Earth Observation PDF Author: Maria Pia Del Rosso
Publisher: IET
ISBN: 1839532122
Category : Computers
Languages : en
Pages : 283

Book Description
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.

Computational Intelligence and Sustainable Systems

Computational Intelligence and Sustainable Systems PDF Author: H. Anandakumar
Publisher: Springer
ISBN: 3030026744
Category : Technology & Engineering
Languages : en
Pages : 304

Book Description
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.

Remote Sensing Image Processing

Remote Sensing Image Processing PDF Author: Gustavo Camps-Valls
Publisher: Springer Nature
ISBN: 3031022475
Category : Technology & Engineering
Languages : en
Pages : 242

Book Description
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