Although Synthetic Aperture Radar (SAR) has been widely used in various forms of mapping for several decades, two factors have created new interest in its utilization for topographic mapping. The first is the emergence of Digital Terrain Models (DTMs) in an ever-increasing range of applications

We propose a method for non-linear data projection that combines Generative Topographic Mapping and Coordinated PCA. We extend the Generative Topographic Mapping by using more complex nodes in the network: each node provides a linear map between the data space and the latent space. The location

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

use one of these algorithms to identify targeted structures within a topographic database (map). We describe a how a problem in topographic datasets is solved using this technique, detailing results on four different datasets. Finally, we outline a variety of other problems that are being addressed

This article  describes how  the University  of North Texas Libraries ’  Digital Projects Unit  used  simple,  freelyavailable APIs  to add place names  to metadata  records  for  over  8,000 maps  in  two digital collections. These textual place names enable users to easily find maps by place name and to find other maps

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We introduce a new unsupervised learning algorithm for kernel-based topographic map formation of heteroscedastic Gaussian mixtures that allows for a unified account of distortion error (vector quantization), log-likelihood and Kullback-Leibler divergence. 1

In this paper, we explain why Scale Space theories do not incorporate obvious restrictions imposed by the physics of image generation [20]. The heat equation #linear scale space# is not contrast invariant and destroys Tjunctions [12]. The same is true for the recently proposed curvature equations #mean curvature motion [2] and affine shortening [27] [2]# : They break the symmetry of junctions #4#. To apply directly these models to natural world images, with occlusions, is therefore impossible. Returning to the original problem of scale space, we show how level lines can be found in an image without smoothing. This makes useless the recourse to a spurious parameter like scale to detect edges.

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Inspired from foregoing analysis of swarm intelligence methods, a novel topographic mapping method is proposed, called Swarm-Organized Pro-jection (SOP). The task of projecting high-dimensional data objects onto a low-dimensional lattice is performed by simulated swarm agents in-spired from