Results 41 to 50 of about 77,938 (282)
Fuzzy Entropy-assisted Fuzzy-Rough Feature Selection [PDF]
2006 IEEE International Conference on Fuzzy Systems, 2006 Feature selection (FS) is a dimensionality reduction technique that aims to select a subset of the original features of a dataset which offer the most useful information. The benefits of feature selection include improved data visualisation, transparency, reduction in training and utilisation times and improved prediction performance.
null Neil Mac Parthalain +2 more
openaire +1 more source
Journal of Applied Mathematics, 2014 In the rough fuzzy set theory, the rough degree is used to characterize the uncertainty of a fuzzy set, and the rough entropy of a knowledge is used to depict the roughness of a rough classification.
Huani Qin, Darong Luo
doaj +1 more source
Finding fuzzy-rough reducts with fuzzy entropy [PDF]
2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence), 2008 Dataset dimensionality is undoubtedly the single most significant obstacle which exasperates any attempt to apply effective computational intelligence techniques to problem domains. In order to address this problem a technique which reduces dimensionality is employed prior to the application of any classification learning.
Neil Mac Parthalain +2 more
openaire +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source
Different Types of Entropy Measures for Type-2 Fuzzy Sets
AxiomsIn this work, we consider De Luca and Termini’s notion of non-probabilistic entropy, and we extend some entropy-like measures of the degree of fuzziness to type-2 fuzzy sets.
Luis Magdalena +3 more
doaj +1 more source
IEEE Access, 2016 Fuzzy entropy and image thresholding are the most direct and effective methods for image segmentation. This paper, taking fuzzy Kapur's entropy as the optimal objective function, with modified discrete Grey wolf optimizer (GWO) as the tool, uses ...
Linguo Li +5 more
doaj +1 more source
Perceptual Copyright Protection Using Multiresolution Wavelet-Based Watermarking And Fuzzy Logic
, 2010 In this paper, an efficiently DWT-based watermarking technique is proposed to embed signatures in images to attest the owner identification and discourage the unauthorized copying.
Hsieh, Ming-Shing
core +3 more sources
Fuzzy Spheres in AdS/CFT Correspondence and Holography from Noncommutativity [PDF]
, 2000 We show that the existent fuzzy S^2 and S^4 models are natural candidates for the quantum geometry on the corresponding spheres in AdS/CFT correspondence. These models fit nicely the data from the dipole mechanism for the stringy exclusion principle.
Banks +25 more
core +2 more sources
Remote Assessment of Ataxia Severity in SCA3 Across Multiple Centers and Time Points
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Spinocerebellar ataxia type 3 (SCA3) is a genetically defined ataxia. The Scale for Assessment and Rating of Ataxia (SARA) is a clinician‐reported outcome that measures ataxia severity at a single time point. In its standard application, SARA fails to capture short‐term fluctuations, limiting its sensitivity in trials.
Marcus Grobe‐Einsler +20 more
wiley +1 more source
Arthritis Care &Research, Accepted Article.Objectives Sjögren's disease is an autoimmune disorder that can impact multiple organ systems, including the peripheral nervous system (PNS). PNS manifestations, which can exist concurrently, include mononeuropathies, polyneuropathies, and autonomic nervous system neuropathies. To help patients and providers in the decision‐making process, we developed
Anahita Deboo +19 more
wiley +1 more source