A New Multi-Sensor Fusion Target Recognition Method Based on Complementarity Analysis and Neutrosophic Set PDF Download
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Author: Yuming Gong
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 18
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Book Description
To improve the efficiency, accuracy, and intelligence of target detection and recognition, multi-sensor information fusion technology has broad application prospects in many aspects. Compared with single sensor, multi-sensor data contains more target information and effective fusion of multi-source information can improve the accuracy of target recognition. However, the recognition capabilities of different sensors are different during target recognition, and the complementarity between sensors needs to be analyzed during information fusion. This paper proposes a multi-sensor fusion recognition method based on complementarity analysis and neutrosophic set. The proposed method mainly has two parts: complementarity analysis and data fusion. Complementarity analysis applies the trained multi-sensor to extract the features of the verification set into the sensor, and obtain the recognition result of the verification set. Based on recognition result, the multi-sensor complementarity vector is obtained. Then the sensor output the recognition probability and the complementarity vector are used to generate multiple neutrosophic sets. Next, the generated neutrosophic sets are merged within the group through the simplified neutrosophic weighted average (SNWA) operator. Finally, the neutrosophic set is converted into crisp number, and the maximum value is the recognition result. The practicality and effectiveness of the proposed method in this paper are demonstrated through examples.
Author: Yuming Gong
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 18
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Book Description
To improve the efficiency, accuracy, and intelligence of target detection and recognition, multi-sensor information fusion technology has broad application prospects in many aspects. Compared with single sensor, multi-sensor data contains more target information and effective fusion of multi-source information can improve the accuracy of target recognition. However, the recognition capabilities of different sensors are different during target recognition, and the complementarity between sensors needs to be analyzed during information fusion. This paper proposes a multi-sensor fusion recognition method based on complementarity analysis and neutrosophic set. The proposed method mainly has two parts: complementarity analysis and data fusion. Complementarity analysis applies the trained multi-sensor to extract the features of the verification set into the sensor, and obtain the recognition result of the verification set. Based on recognition result, the multi-sensor complementarity vector is obtained. Then the sensor output the recognition probability and the complementarity vector are used to generate multiple neutrosophic sets. Next, the generated neutrosophic sets are merged within the group through the simplified neutrosophic weighted average (SNWA) operator. Finally, the neutrosophic set is converted into crisp number, and the maximum value is the recognition result. The practicality and effectiveness of the proposed method in this paper are demonstrated through examples.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 411
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Book Description
This volume presents state-of-the-art papers on new topics related to neutrosophic theories, such as neutrosophic algebraic structures, neutrosophic triplet algebraic structures, neutrosophic extended triplet algebraic structures, neutrosophic algebraic hyperstructures, neutrosophic triplet algebraic hyperstructures, neutrosophic n-ary algebraic structures, neutrosophic n-ary algebraic hyperstructures, refined neutrosophic algebraic structures, refined neutrosophic algebraic hyperstructures, quadruple neutrosophic algebraic structures, refined quadruple neutrosophic algebraic structures, neutrosophic image processing, neutrosophic image classification, neutrosophic computer vision, neutrosophic machine learning, neutrosophic artificial intelligence, neutrosophic data analytics, neutrosophic deep learning, and neutrosophic symmetry, as well as their applications in the real world.
Author: Jukka Heikkonen
Publisher: Mdpi AG
ISBN: 9783036513522
Category : Mathematics
Languages : en
Pages : 168
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Book Description
Application of multi-sensor fusion technology has drawn a lot of industrial and academic interest in recent years. The multi-sensor fusion methods are widely used in many applications, such as autonomous systems, remote sensing, video surveillance, and the military. These methods can obtain the complementary properties of targets by considering multiple sensors. On the other hand, they can achieve a detailed environment description and accurate detection of interest targets based on the information from different sensors. This book collects novel developments in the field of multi-sensor, multi-source, and multi-process information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Published papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems.
Author: Rae Yoon Park
Publisher:
ISBN:
Category :
Languages : en
Pages : 372
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Book Description
Author: Ivan Kadar
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 600
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Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 3
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Book Description
The research funded under this grant focused on several key challenges arising in automatic target recognition (ATR) systems. The robust estimation of geometric features is a critical aspect of ATR systems and thus methods for robust boundary extraction and feature enhancement were developed based on both statistical modeling and compressed sensing. Another set of challenges was related to novel, non-conventional sensing geometries arising in modern layered-sensing systems. Traditional sensing has focused on single sensors and single aspects, e.g. conventional mono-static, narrow aspect SAR. But as new sensing paradigms are considered, new methods for image estimation and processing are needed. In response, novel, robust methods for wide-angle image formation and multi-static multi-sensor data fusion were developed, based on powerful sparsity constraints. In addition, recent methods from compressed sensing were applied to SAR imaging problems of interest to the Air Force to reduce sampling requirements and improve robustness. Finally, imaging of scenes with moving targets has become a problem of great interest to AFRL. In response new methods for the formation and treatment of scenes with motion were developed based on over complete dictionaries.
Author: Xue-Bo Jin
Publisher: MDPI
ISBN: 3039283022
Category : Technology & Engineering
Languages : en
Pages : 602
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Book Description
This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 143
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Book Description
We introduce for the first time the concept of plithogeny in philosophy and, as a derivative, the concepts of plithogenic set / logic / probability / statistics in mathematics and engineering – and the degrees of contradiction (dissimilarity) between the attributes’ values that contribute to a more accurate construction of plithogenic aggregation operators and to the plithogenic relationship of inclusion (partial ordering).
Author: Florentin Smarandache
Publisher: Infinite Study
ISBN: 1599730804
Category : Mathematics
Languages : en
Pages : 157
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Book Description
N-Norm and N-conorm are extended in Neutrosophic Logic/Set.
Author: Florentin Smarandache
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 110
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Book Description
