Add to ORKGIn this paper, a hybrid intelligent system that integrates the SOM (Self-Organizing Map) neural network, kMER (kernel-based Maximum Entropy learning Rule), and Probabilistic Neural Network (PNN) for data visualization and classification is proposed. The rationales of this Probabilistic SOM-kMER model are explained, and its applicability is demonstrated using two benchmark data sets. The results are analyzed and compared with those from a number of existing methods. Implication of the proposed hybrid system as a useful and usable data visualization and classification tool is discussed.<br /
We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification...
Heidemann G, Saalbach A, Ritter H. Semi-automatic acquisition and labeling of image data using SOMs....
Data with dimension higher than three is not possible to be visualized directly. Unfortunately in re...
Abstract:- In this paper, a hybrid intelligent system that integrates the SOM (Self-Organizing Map) ...
This paper proposes a hybrid system that integrates the SOM (Self Organizing Map) neural network, th...
Tesis ini mempersembahkan penyelidikan tentang satu model hibrid rangkaian neural buatan yang boleh ...
We present a new hybrid neural network to perform the probabilistic classification of medical images...
International audienceIn classification problem, several different classes may be partially overlapp...
This thesis looks into the methodologies of implementing hybrid neural network for data classificati...
This paper first studies the generalization ability of the convolutional layer as a feature mapper (...
This paper proposes an hybrid artificial neural network (ANN) with self-organizing map (SOM) and mod...
Classification tasks are an integral part of science, industry, business, and health care systems; b...
A review of recent development of the self-organising map (SOM) for applications related to data map...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
Classification tasks are an integral part of science, industry, medicine, and business; being such a...
We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification...
Heidemann G, Saalbach A, Ritter H. Semi-automatic acquisition and labeling of image data using SOMs....
Data with dimension higher than three is not possible to be visualized directly. Unfortunately in re...
Abstract:- In this paper, a hybrid intelligent system that integrates the SOM (Self-Organizing Map) ...
This paper proposes a hybrid system that integrates the SOM (Self Organizing Map) neural network, th...
Tesis ini mempersembahkan penyelidikan tentang satu model hibrid rangkaian neural buatan yang boleh ...
We present a new hybrid neural network to perform the probabilistic classification of medical images...
International audienceIn classification problem, several different classes may be partially overlapp...
This thesis looks into the methodologies of implementing hybrid neural network for data classificati...
This paper first studies the generalization ability of the convolutional layer as a feature mapper (...
This paper proposes an hybrid artificial neural network (ANN) with self-organizing map (SOM) and mod...
Classification tasks are an integral part of science, industry, business, and health care systems; b...
A review of recent development of the self-organising map (SOM) for applications related to data map...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
Classification tasks are an integral part of science, industry, medicine, and business; being such a...
We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification...
Heidemann G, Saalbach A, Ritter H. Semi-automatic acquisition and labeling of image data using SOMs....
Data with dimension higher than three is not possible to be visualized directly. Unfortunately in re...