Results 1  10
of
841,475
Computing Degrees of Subsethood and Similarity for IntervalValued Fuzzy Sets: Fast Algorithms
"... Abstract—Subsethood A ⊆ B and set equality A = B are among the basic notions of set theory. For traditional (“crisp”) sets, every element a either belongs to a set A or it does not belong to A, and for every two sets A and B, either A ⊆ B or A � ⊆ B. To describe commonsense and expert reasoning, it ..."
Abstract

Cited by 6 (0 self)
 Add to MetaCart
definite membership degree µA(a) to each element a; it is more realistic to expect that an expert describes an interval [µ A (a), µ A (a)] of possible values of this degree. The resulting intervalvalued fuzzy set can be viewed as a class of all possible fuzzy sets µA(a) ∈ [µ A (a), µ A (a)]. For intervalvalued
Subsethoodbased Fuzzy Modelling and Classification
"... Reasoning with fuzzy rulebased models has been widely applied to perform various real world classification tasks. The main advantage of this approach is that it supports inferences in the way people think and make judgements. However, in order to gain high classification accuracy, transparency and ..."
Abstract
 Add to MetaCart
Reasoning with fuzzy rulebased models has been widely applied to perform various real world classification tasks. The main advantage of this approach is that it supports inferences in the way people think and make judgements. However, in order to gain high classification accuracy, transparency
FuzzySubsethood based Color Image Processing
"... This paper presents the exploitation of the concept of fuzzysubsethood for defining a new class of color image processing operations. By considering a color value as a fuzzy set, the calculus of fuzzysubsethood becomes applicable to color images. From this, a simple color threshold operation c ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
This paper presents the exploitation of the concept of fuzzysubsethood for defining a new class of color image processing operations. By considering a color value as a fuzzy set, the calculus of fuzzysubsethood becomes applicable to color images. From this, a simple color threshold operation
Intervalvalued fuzzy clustering
"... In this work we propose an objective function to obtain an intervalvalued fuzzy clustering. After the process of optimization we obtain an intervalvalued fuzzy partition in which the length of the intervals depends on the position of the points with respect of the clusters. ..."
Abstract
 Add to MetaCart
In this work we propose an objective function to obtain an intervalvalued fuzzy clustering. After the process of optimization we obtain an intervalvalued fuzzy partition in which the length of the intervals depends on the position of the points with respect of the clusters.
Histograms of Oriented Gradients for Human Detection
 In CVPR
, 2005
"... We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of Histograms of Oriented Gradient (HOG) descriptors significantly out ..."
Abstract

Cited by 3678 (9 self)
 Add to MetaCart
We study the question of feature sets for robust visual object recognition, adopting linear SVM based human detection as a test case. After reviewing existing edge and gradient based descriptors, we show experimentally that grids of Histograms of Oriented Gradient (HOG) descriptors significantly
Community detection in graphs
, 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
Abstract

Cited by 801 (1 self)
 Add to MetaCart
The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such
An intrusiondetection model
 IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1987
"... A model of a realtime intrusiondetection expert system capable of detecting breakins, penetrations, and other forms of computer abuse is described. The model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of sy ..."
Abstract

Cited by 632 (0 self)
 Add to MetaCart
A model of a realtime intrusiondetection expert system capable of detecting breakins, penetrations, and other forms of computer abuse is described. The model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns
A computational approach to edge detection
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1986
"... AbstractThis paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal ..."
Abstract

Cited by 4621 (0 self)
 Add to MetaCart
AbstractThis paper describes a computational approach to edge detection. The success of the approach depends on the definition of a comprehensive set of goals for the computation of edge points. These goals must be precise enough to delimit the desired behavior of the detector while making minimal
How Iris Recognition Works
, 2003
"... Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in six field and laboratory trials, producing no false matches in several million comparison tests. The recognition principle is the failure of a test of statistical independence on iris phase st ..."
Abstract

Cited by 495 (4 self)
 Add to MetaCart
”) or few comparisons. This paper explains the algorithms for iris recognition, and presents the results of 2.3 million comparisons among eye images acquired in trials in Britain, the USA, and Japan. 1
Singularity Detection And Processing With Wavelets
 IEEE Transactions on Information Theory
, 1992
"... Most of a signal information is often found in irregular structures and transient phenomena. We review the mathematical characterization of singularities with Lipschitz exponents. The main theorems that estimate local Lipschitz exponents of functions, from the evolution across scales of their wavele ..."
Abstract

Cited by 590 (13 self)
 Add to MetaCart
of their wavelet transform are explained. We then prove that the local maxima of a wavelet transform detect the location of irregular structures and provide numerical procedures to compute their Lipschitz exponents. The wavelet transform of singularities with fast oscillations have a different behavior that we
Results 1  10
of
841,475