Results 101 to 110 of about 9,780 (156)

On modal logic interpretation of Dempster–Shafer theory of evidence

International Journal of Intelligent Systems, 1994
Summary: This article further develops one branch of research initiated in an article by \textit{G. Resconi}, \textit{G. J. Klir} and \textit{U. St. Clair}, Int. J. Gen. Syst., 21, No. 1, 23-50 (1992; Zbl 0767.03008) and continued in another article by the same authors [Int. J. Uncertainty, Fuzziness and Knowledge-Based Systems, 1, No. 1, 1-18 (1993)].
Harmanec, David, Klir, George J., Resconi, Germano   +2 more
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Color image segmentation based on Dempster-Shafer evidence theory

MELECON 2008 - The 14th IEEE Mediterranean Electrotechnical Conference, 2008
In this paper, a color image segmentation approach based on Dempster-Shafer evidence theory is presented. The basic technique consists in combining information coming from three independent information sources for the same image. These sources correspond to the three component images R (red), G (green) and B (blue).
S. Ben Chaabane, M. Sayadi, F. Fnaiech, E. Brassart   +3 more
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Epistemic Probability: the Dempster-Shafer theory of evidence

1993
We mentioned in Chapter 2 the distinction between subjective and objective probability; two different interpretations of essentially the same mathematical formalism. This sharing of the use of the word ‘probability’ in the naming of both interpretations has led to an unfortunate confounding of two different concepts. The development of the mathematical
Paul Krause, Dominic Clark
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Dempster–Shafer evidence theory approach to structural damage detection

Structural Health Monitoring, 2011
In this study, the Dempster–Shafer (D–S) evidence theory-based approach for structural damage detection is presented. First, the damage basic probability assignment (BPA) function of substructures using each data set measured from the monitored structure is calculated.
Yuequan Bao, Hui Li, Yonghui An, Jinping Ou   +3 more
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Dempster-Shafer evidence theory for multi-bearing faults diagnosis

Engineering Applications of Artificial Intelligence, 2017
Support vector machines (SVMs) are frequently used in automated machinery faults diagnosis to classify multiple machinery faults by handling a high number of input features with low sampling data sets. SVMs are well known for fault detection that involves binary fault classifications only (i.e., healthy vs. faulty).
Kar, Hoou Hui, Meng, Hee Lim, Ali Al-Obaidi, Salah Mahdi, Leong, Mohd. Salman @ Yew Mun   +3 more
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Combining Evidence in the Extended Dempster-Shafer Theory

1990
The Dempster-Shafer (D-S) theory of evidence generalizes Bayesian probability theory, by providing a coherent representation for ignorance (lack of evidence). However, uncertain relationships between evidence and hypotheses bearing on this evidence are difficult to represent in applications of the theory.
Jiwen Guan, Jasmina Pavlin, Victor R. Lesser   +2 more
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Enhanced Metric Learning via Dempster-Shafer Evidence Theory

2018
Metric learning is a hot topic in machine learning. A proper learned metric can measure the similarity between samples better and hence significantly improves the performance of machine learning algorithm. In this paper, we propose a novel enhanced distance metric learning method via Dempster-Shafer (D-S) evidence theory.
Ying Li, Yabo Zhang, Yaxin Peng
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Multi-scale data fusion using Dempster-Shafer evidence theory

IEEE International Geoscience and Remote Sensing Symposium, 2003
In the remote sensing domain, the combination of multi-scale satellite data appears as a new challenge for the signal processing community. This approach will lead to strong advances in Earth monitoring and continental land cover classifications by use of the complementary of the data presenting either high spatial resolution or high time ...
Le Hégarat-Mascle, S., Richard, D., Ottlé, C.   +2 more
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Image Subcategory Classification Based on Dempster-Shafer Evidence Theory

2012 International Conference on Computer Science and Service System, 2012
Traditional image subcategory classification methods combined multiple features into a feature vector. Such methods neglect distinct roles of diverse features on discriminating image subcategories. In this paper, the Dempster-Shafer evidence theory is applied to fuse different features in image subcategory classification.
Haidi Gao, Xiangjun Shen, Zhongqiu Jiang, Hebiao Yang, Li Yan   +4 more
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