This paper deals with the Kohonen Self-organizing maps for cluster analysis applications. The cluster analysis represents a group of methods whose aim is to classify the objects into clusters. For solving cluster analysis applications many new algorithms using neural networks have been used. This paper describes the use of an advanced method of neural network represented by Kohonen self-organiz...

In this paper, we propose a new image compression algorithm based on Kohonen self-organized maps. The compression is based on vector quantization (VQ) of the DCT coefficients of image blocks, where the VQ is implemented by a Kohonen network. At low bitrates, our proposed method performs better than an earlier compression scheme developed by Amerijckx et al. [1] and shows better subjective resul...

In this paper, we propose a new model for two purposes: (1) discovering communities of users on social networks via topics with the temporal factor and (2) analyzing the changes in interested topics and users in communities in each period of time. This model, we use Kohonen network (SelfOrganizing Map) combining with the topic model. After discovering communities, results are shown on output la...

In this paper, we present Kohonen Self-Organizing Feature Maps (SOMs) as a method for automatically nding classes of dialogue utterances on the basis of superrcial utterance features, in particular for dialogues found in the Schisma corpus. Furthermore, we discuss some ways for determining the quality of a certain utterance classiication. We propose to use supervised classiication to gain more ...

Priyanka Khandelwal , Krishna Kant Singh , B.K.Singh , Akansha Mehrotra 1 Electronics & Communication Engineering, BTKIT, Dwarhat, India 2 Earthquake Engineering, IIT, Roorkee, India 1 [email protected] [email protected] 2 [email protected] [email protected] Abstract— In this paper, an unsupervised change detection technique of multispectral images based on wavelet fusion ...

We describe an application of 1-Dimensional Kohonen Networks to the classification of color 2D images which has been evaluated in Popocatépetl Volcano’s images. The Popocatépetl, located in the limits of the State of Puebla in México, is active and under monitoring since 1997. We address the question if our application of the Kohonen Network classifies according to the total intensity color of ...

It is well known that the SOM algorithm achieves a clustering of data which can be interpreted as an extension of Principal Component Analysis, because of its topologypreserving property. But the SOM algorithm can only process real-valued data. In previous papers, we have proposed several methods based on the SOM algorithm to analyze categorical data, which is the case in survey data. In this p...