Application Of Dsmt Icm With Adaptive Decision Rule To Supervised Classi Cation In Multisource Remote Sensing
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Application Of Dsmt Icm With Adaptive Decision Rule To Supervised Classi Cation In Multisource Remote Sensing
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Author : A. Elhassouny
language : en
Publisher: Infinite Study
Release Date :
Application Of Dsmt Icm With Adaptive Decision Rule To Supervised Classi Cation In Multisource Remote Sensing written by A. Elhassouny and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
In this paper, we introduce a new procedure called DSmT-ICM with adaptive decision rule, which is an alternative and extension of Multisource Classification Using ICM (Iterated conditional mode) and DempsterShafer theory (DST). This work confirmed the ability of the Dezert-Smarandache Theory (DSmT) used for the modeling of the classes sets of themes to significantly improve the quality of ICM classification algorithm with constraints by the fusion of the multidates images.
Advances And Applications Of Dsmt For Information Fusion Vol Iv
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Author : Florentin Smarandache, Jean Dezert
language : en
Publisher: Infinite Study
Release Date : 2015-03-01
Advances And Applications Of Dsmt For Information Fusion Vol Iv written by Florentin Smarandache, Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-01 with categories.
The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) ininternational conferences, seminars, workshops and journals.
Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2023-12-27
Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 5 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-27 with Biography & Autobiography categories.
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 (available at fs.unm.edu/DSmT-book4.pdf or www.onera.fr/sites/default/files/297/2015-DSmT-Book4.pdf) in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well. We want to thank all the contributors of this fifth volume for their research works and their interests in the development of DSmT, and the belief functions. We are grateful as well to other colleagues for encouraging us to edit this fifth volume, and for sharing with us several ideas and for their questions and comments on DSmT through the years. We thank the International Society of Information Fusion (www.isif.org) for diffusing main research works related to information fusion (including DSmT) in the international fusion conferences series over the years. Florentin Smarandache is grateful to The University of New Mexico, U.S.A., that many times partially sponsored him to attend international conferences, workshops and seminars on Information Fusion. Jean Dezert is grateful to the Department of Information Processing and Systems (DTIS) of the French Aerospace Lab (Office National d’E´tudes et de Recherches Ae´rospatiales), Palaiseau, France, for encouraging him to carry on this research and for its financial support. Albena Tchamova is first of all grateful to Dr. Jean Dezert for the opportunity to be involved during more than 20 years to follow and share his smart and beautiful visions and ideas in the development of the powerful Dezert-Smarandache Theory for data fusion. She is also grateful to the Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, for sponsoring her to attend international conferences on Information Fusion.
Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 4
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2015-07-01
Advances And Applications Of Dsmt For Information Fusion Collected Works Volume 4 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-01 with Mathematics categories.
The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions have been published or presented after disseminating the third volume (2009, http://fs.gallup.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals.
Improvement Of Multimodal Images Classification Based On Dsmt Using Visual Saliency Model Fusion With Svm
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Author : Hanan Anzid
language : en
Publisher: Infinite Study
Release Date :
Improvement Of Multimodal Images Classification Based On Dsmt Using Visual Saliency Model Fusion With Svm written by Hanan Anzid and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Multimodal images carry available information that can be complementary, redundant information, and overcomes the various problems attached to the unimodal classification task, by modeling and combining these information together. Although, this classification gives acceptable classification results, it still does not reach the level of the visual perception model that has a great ability to classify easily observed scene thanks to the powerful mechanism of the human brain.
Fusion D Images
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Author : Azeddine Elhassouny
language : fr
Publisher: Infinite Study
Release Date : 2015-05-26
Fusion D Images written by Azeddine Elhassouny and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-26 with categories.
Au cours de la dernière décennie, l'observation de la Terre depuis l'espace s'est amplement développée, comme l'a rme la grande quantité de satellites imageurs mis sur orbite. De plus, les satellites imageurs peuvent couvrir de larges zones de façon régulière, ce qui garantit la disponibilité de données pour la cartographie.
Neutrosophy
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Author : Florentin Smarandache
language : en
Publisher:
Release Date : 1998
Neutrosophy written by Florentin Smarandache and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.
Marine Artillery Survey Operations
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Author : U. S. Corps
language : en
Publisher: CreateSpace
Release Date : 2013-06-27
Marine Artillery Survey Operations written by U. S. Corps and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-27 with categories.
Marine Corps Warfighting Publication (MCWP) 3-16.7, Marine Artillery Survey Operations, sets forth the doctrinal foundation and technical information that Marines need to provide accurate and timely survey support.
Kernel Methods For Remote Sensing Data Analysis
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Author : Gustau Camps-Valls
language : en
Publisher: John Wiley & Sons
Release Date : 2009-09-03
Kernel Methods For Remote Sensing Data Analysis written by Gustau Camps-Valls 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 2009-09-03 with Technology & Engineering categories.
Kernel methods have long been established as effective techniques in the framework of machine learning and pattern recognition, and have now become the standard approach to many remote sensing applications. With algorithms that combine statistics and geometry, kernel methods have proven successful across many different domains related to the analysis of images of the Earth acquired from airborne and satellite sensors, including natural resource control, detection and monitoring of anthropic infrastructures (e.g. urban areas), agriculture inventorying, disaster prevention and damage assessment, and anomaly and target detection. Presenting the theoretical foundations of kernel methods (KMs) relevant to the remote sensing domain, this book serves as a practical guide to the design and implementation of these methods. Five distinct parts present state-of-the-art research related to remote sensing based on the recent advances in kernel methods, analysing the related methodological and practical challenges: Part I introduces the key concepts of machine learning for remote sensing, and the theoretical and practical foundations of kernel methods. Part II explores supervised image classification including Super Vector Machines (SVMs), kernel discriminant analysis, multi-temporal image classification, target detection with kernels, and Support Vector Data Description (SVDD) algorithms for anomaly detection. Part III looks at semi-supervised classification with transductive SVM approaches for hyperspectral image classification and kernel mean data classification. Part IV examines regression and model inversion, including the concept of a kernel unmixing algorithm for hyperspectral imagery, the theory and methods for quantitative remote sensing inverse problems with kernel-based equations, kernel-based BRDF (Bidirectional Reflectance Distribution Function), and temperature retrieval KMs. Part V deals with kernel-based feature extraction and provides a review of the principles of several multivariate analysis methods and their kernel extensions. This book is aimed at engineers, scientists and researchers involved in remote sensing data processing, and also those working within machine learning and pattern recognition.