Object identification using T-conorm/norm fusion rule PDF Download
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Author: Albena Tchamova
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 10
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Book Description
This small chapter presents an approach providing fast reduction of total ignorance in the process of target identification. It utilizes the recently defined fusion rule based on fuzzy T-conorm/Tnorm operators, as well as all the available information from the adjoint sensor and additional information obtained from the a priori defined objective and subjective considerations, concerning relationships between the attribute components at different levels of abstraction.
Author: Albena Tchamova
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 10
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Book Description
This small chapter presents an approach providing fast reduction of total ignorance in the process of target identification. It utilizes the recently defined fusion rule based on fuzzy T-conorm/Tnorm operators, as well as all the available information from the adjoint sensor and additional information obtained from the a priori defined objective and subjective considerations, concerning relationships between the attribute components at different levels of abstraction.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN: 1599730731
Category : Science
Languages : en
Pages : 760
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Book Description
This volume has about 760 pages, split into 25 chapters, from 41 contributors. First part of this book presents advances of Dezert-Smarandache Theory (DSmT) which is becoming one of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache¿s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule. A new probabilistic transformation of mass of belief is also presented which outperforms the classical pignistic transformation in term of probabilistic information content. The second part of the book presents applications of DSmT in target tracking, in satellite image fusion, in snow-avalanche risk assessment, in multi-biometric match score fusion, in assessment of an attribute information retrieved based on the sensor data or human originated information, in sensor management, in automatic goal allocation for a planetary rover, in computer-aided medical diagnosis, in multiple camera fusion for tracking objects on ground plane, in object identification, in fusion of Electronic Support Measures allegiance report, in map regenerating forest stands, etc.
Author: Albena Tchamova
Publisher: Infinite Study
ISBN:
Category :
Languages : en
Pages : 11
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Book Description
In this paper the behavior of three combinational rules for temporal/ sequential attribute data fusion for target type estimation are analyzed. The comparative analysis is based on: Dempster’s fusion rule proposed in Dempster-Shafer Theory.
Author: Florentin Smarandache, Jean Dezert
Publisher: Infinite Study
ISBN: 1599733242
Category :
Languages : en
Pages : 506
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Book Description
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.
Author: James C. Bezdek
Publisher: Springer Science & Business Media
ISBN: 0387245790
Category : Computers
Languages : en
Pages : 786
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Book Description
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Unique to this volume in the Kluwer Handbooks of Fuzzy Sets Series is the fact that this book was written in its entirety by its four authors. A single notation, presentation style, and purpose are used throughout. The result is an extensive unified treatment of many fuzzy models for pattern recognition. The main topics are clustering and classifier design, with extensive material on feature analysis relational clustering, image processing and computer vision. Also included are numerous figures, images and numerical examples that illustrate the use of various models involving applications in medicine, character and word recognition, remote sensing, military image analysis, and industrial engineering.
Author: Pinakpani Pal
Publisher: World Scientific
ISBN: 9814475963
Category : Computers
Languages : en
Pages : 444
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Book Description
This volume contains the latest in the series of ICAPR proceedings on the state-of-the-art of different facets of pattern recognition. These conferences have already carved out a unique position among events attended by the pattern recognition community. The contributions tackle open problems in the classic fields of image and video processing, document analysis and multimedia object retrieval as well as more advanced topics in biometrics speech and signal analysis. Many of the papers focus both on theory and application driven basic research pattern recognition.
Author:
Publisher: 清华大学出版社有限公司
ISBN: 9787302113775
Category : Computational intelligence
Languages : en
Pages : 594
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Book Description
Author: Firooz A. Sadjadi
Publisher: SPIE-International Society for Optical Engineering
ISBN:
Category : Computers
Languages : en
Pages : 636
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Book Description
This text presents papers covering issues in the field of sensor and data fusion. Topics include: classifier integration with multiple sensors; combining uncertain messages using belief functions; decentralized sequential detection; and fusion, propagation, and structuring belief networks.
Author: Edwin Lughofer
Publisher: Springer
ISBN: 3030056457
Category : Technology & Engineering
Languages : en
Pages : 564
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Book Description
This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power.
Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3030341356
Category : Technology & Engineering
Languages : en
Pages : 354
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Book Description
This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.
