Add to ORKGNew pattern recognition method is considered that is based on weighted voting by systems of subregions if feature space. Optimal subregion «syndromes» are searched with the help of optimal partitioning inside several families of different complexity levels. Results of experiments are represented
Local learning methods approximate a target function (a posteriori probability) by partitioning the ...
International audienceThis article introduces the problem of searching locally optimal patterns with...
The paper presents a methodology to evaluate and compare different algorithms for general pattern re...
New pattern recognition method is considered that is based on weighted voting by systems of subregio...
In this work the new pattern recognition method based on the unification of algebraic and statistica...
The methods suggested make it possible to find clasters with the given properties and to optimize se...
In pattern recognition, there is a growing use of multiple classifier combinations with the goal to ...
<p>Recognition results of 45 two-class tasks by the optimally-dependent v.s. fully-dependent and nei...
We propose a novel method for recognizing sequential patterns such as motion trajectory of biologica...
Abstract—Recently, it has been demonstrated that combining the decisions of several classifiers can ...
Systems for assessing the classification complexity of a dataset have received increasing attention...
In pattern recognition, the approach where Supervised Learning is reduced to the construction of dec...
The Subspace Pattern Recognition Method (SPRM) is a statistical method where each class is represent...
Pattern recognition systems play a role in applications as diverse as speech recognition, optical ch...
This monograph deals with mathematical constructions that are foundational in such an important area...
Local learning methods approximate a target function (a posteriori probability) by partitioning the ...
International audienceThis article introduces the problem of searching locally optimal patterns with...
The paper presents a methodology to evaluate and compare different algorithms for general pattern re...
New pattern recognition method is considered that is based on weighted voting by systems of subregio...
In this work the new pattern recognition method based on the unification of algebraic and statistica...
The methods suggested make it possible to find clasters with the given properties and to optimize se...
In pattern recognition, there is a growing use of multiple classifier combinations with the goal to ...
<p>Recognition results of 45 two-class tasks by the optimally-dependent v.s. fully-dependent and nei...
We propose a novel method for recognizing sequential patterns such as motion trajectory of biologica...
Abstract—Recently, it has been demonstrated that combining the decisions of several classifiers can ...
Systems for assessing the classification complexity of a dataset have received increasing attention...
In pattern recognition, the approach where Supervised Learning is reduced to the construction of dec...
The Subspace Pattern Recognition Method (SPRM) is a statistical method where each class is represent...
Pattern recognition systems play a role in applications as diverse as speech recognition, optical ch...
This monograph deals with mathematical constructions that are foundational in such an important area...
Local learning methods approximate a target function (a posteriori probability) by partitioning the ...
International audienceThis article introduces the problem of searching locally optimal patterns with...
The paper presents a methodology to evaluate and compare different algorithms for general pattern re...