we introduce a form of non-linear latent variable model called the Generative Topographic Mapping for which the parameters of the model can be determined using the EM algorithm. GTM provides a principled alternative to the widely used Self-Organizing Map (SOM) of Kohonen (1982), and overcomes most

of Gaetano Kanizsa according to which visual perception tends to remain stable with respect to these basic operations. We define a contrast invariant presentation of the digital image, the topographic map, where the subjacent occlusion-transparency structure is put into evidence by the interplay of level

Automated evaluation of generalized topographic maps — supported by formalization and data enrichment techniques

We address the problem of extending topographic maps to color images. A topographic map gives a morphological and a geometrical representation of the information contained in natural images. Two approaches are presented and discussed. The first one is new and consists in defining a total order

setting(7) to give the GTM (Generative Topographic Mapping). In going to a probabilistic formulation, several limitations of the SOM were overcome, including the absence of a cost function and thelack of a convergence proof.

Abstract. A kernel version of Generative Topographic Mapping, a model of the manifold learning family, is defined in this paper. Its ability to adequately model non-i.i.d. data is illustrated in a problem concerning the identification of protein subfamilies from protein sequences. 1

www.newtopo.co.nz Current technologies have given us opportunities to explore and develop the graphic communication of topographic mapping. This paper presents some developments within a New Zealand mountain context, and challenges cartographers to further improve effective communication through

Abstract-This paper describes Latent Beta Topographic Mapping (LBTM), a generative probability model for non linear dimensionality reduction and density estimation. LBTM is based on Generative Topographic Mapping (GTM) and hence inherits its ability to map complex non linear manifolds. However

ABSTRACT. The investigation of interpretability of panchromatic satellite image IRS-1C inte-grated with multispectral Landsat TM image with the purpose of updating the topographic map sheet at the scale of 1:25 000 has been described. The geocoding of source map was based on trigonometric points

Abstract. The generative topographic mapping (GTM) has been proposed as a statistical modeltorepresent highdimensional databymeans of a sparse lattice of points in latent space, such that visualization, compression, and data inspection become possible. Original GTM is restricted to Euclidean data