Data fusion in robotics and machine intelligence
Data fusion in robotics and machine intelligence
The representation of importance and interaction of features by fuzzy measures
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
The Choquet integral for the aggregation of interval scales in multicriteria decision making
Fuzzy Sets and Systems - Special issue: Preference modelling and applications
On naive Bayesian fusion of dependent classifiers
Pattern Recognition Letters
Choquet fuzzy integral based modeling of nonlinear system
Applied Soft Computing
Non-atomicity for fuzzy and non-fuzzy multivalued set functions
Fuzzy Sets and Systems
A novel cell segmentation method and cell phase identification using Markov model
IEEE Transactions on Information Technology in Biomedicine
International Journal of Approximate Reasoning
Face recognition using fuzzy Integral and wavelet decomposition method
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Feature interaction in subspace clustering using the Choquet integral
Pattern Recognition
Personalized identification of abdominal wall hernia meshes on computed tomography
Computer Methods and Programs in Biomedicine
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The paradigm of the permanence of updating ratios, which is a well-proven concept in experimental engineering approximation, has recently been utilized to construct a probabilistic fusion approach for combining knowledge from multiple sources. This ratio-based probabilistic fusion, however, assumes the equal contribution of attributes of diverse evidences. This paper introduces a new framework of a fuzzy probabilistic data fusion using the principles of the permanence of ratios paradigm, and the theories of fuzzy measures and fuzzy integrals. The fuzzy sub-fusion of the proposed approach allows an effective model for incorporating evidence importance and interaction.