نتایج جستجو برای: نگاشت خودسازمانده som
تعداد نتایج: 11551 فیلتر نتایج به سال:
We present a new neural classification model called Concurrent Self-Organizing Maps (CSOM), representing a winner-takes-all collection of small SOM networks. Each SOM of the system is trained individually to provide best results for one class only. We have considered two significant applications: face recognition and multispectral satellite image classification. For first application, we have u...
The Self-Organizing Map (SOM) is a powerful tool in the exploratory phase of data mining. It is capable of projecting high-dimensional data onto a regular, usually 2dimensional grid of neurons with good neighborhood preservation between two spaces. However, due to the dimensional conflict, the neighborhood preservation cannot always lead to perfect topology preservation. In this paper, we estab...
The effect of decomposition and diagenesis of sediment organic matter (SOM) on the adsorption of emerging pollutants by the sediment has been seldom addressed. In the present experimental study, artificial sediment was incubated to simulate the natural organic diagenesis process and hence investigate the influence of organic diagenesis on the adsorption of tetracyclines (TCs) by marine sediment...
Protein fold classification is an important problem in bioinformatics and a challenging task for machine-learning algorithms. In this paper we present a solution which classifies protein folds using Kohonen’s Self-Organizing Map (SOM) and a comparison between few approaches for protein fold classification. We use SOM, Fisher Linear Discriminant Analysis (FLD), K-Nearest Neighbour (KNN), Support...
This paper describes the application of the Self-Organizing Map (SOM) in visual exploration of physical geography data. The main justifications for the application of SOM in this issue is that its stresses local factors and topological order. Public domain thematic maps from Portuguese Environment Institute are used. An adequate geospatial unfolding of SOM is presumed to assist a better represe...
It is expected that the agricultural intensification occurred in recent decades in the Argentine Rolling Pampa significantly alters the SOM reserves. Therefore, it is necessary to identify soil organic carbon (C) and nitrogen (N) fractions to understand the functionality and stabilization of these reserves. Our objectives were to study the NT effect in two crop rotations, corn-double cropped wh...
This paper presents a constrained self-organizing map (SOM) model for the visualization and reconstruction of the human brain lateral ventricle. The SOM model is a widely used method to approximate large and complex high dimensional data and reduce the data dimension for advanced applications. In our applications, the SOM model is used to deform a spherical network field to a 3D crooked brain ...
In this paper we investigate the performance of the Kohonen’s self organizing map (SOM) as a strategy for the analysis of multispectral and multi-resolution remote sensed images. The paper faces the problem of data fusion, by extracting and combining multi-spectral and textural features. Moreover we address the problem of low-quantity and low-quality of labelled pixels in the training set, inve...
Somatostatin-producing neuroendocrine tumors (SOM-NETs) of the duodenum and pancreas appear to be heterogeneous. To determine their clinicopathological profiles, respective data were analyzed on a series of 82 duodenal and 541 pancreatic NETs. In addition, the clinical records of 821 patients with duodenal or pancreatic NETs were reviewed for evidence of a somatostatinoma syndrome. Predominant ...
The Self-Organizing Map (SOM) is an artificial neural network that is very effective for clustering via visualization. Ideally, so as produce a good model, the output space dimension of the SOM should match the intrinsic dimension of the data. However, because it is very difficult or even impossible to visualize SOM’s with more than two dimensions, the vast majority of applications use SOM with...
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