Planning most-likely paths from overhead imagery

This paper is about planning paths from overhead imagery, the novelty of which is taking explicit account of uncertainty in terrain classification and spatial variation in terrain cost. The image is first classified using a multi-class Gaussian Process Classifier which provides probabilities of class membership at each location in the image. The probability of class membership at a particular grid location is then combined with a terrain cost evaluated at that location using a spatial Gaussian process. The resulting cost function is, in turn, passed to a planner. This allows both the uncertainty in terrain classification and spatial variations in terrain costs to be incorporated into the planned path. Because the cost of traversing a grid cell is now a probability density rather than a single scalar value, we can produce not only the most-likely shortest path between points on the map, but also sample from the cost map to produce a distribution of paths between the points. Results are shown in the form of planned paths over aerial maps, these paths are shown to vary in response to local variations in terrain cost.

Internet usage, internet intensity and international sales performance SME's : a structural model approach

There has been much written about the Internet’s potential to enhance international market growth opportunities for SME’s. However, the literature is vague as to how Internet usage and the application of Internet marketing also known as Internet marketing intensity has an impact on firm international market growth. This paper examines the level and role of the Internet in the international operations of a sample of 218 Australian SMEs with international customers. This study shows evidence of a statistical relationship between Internet usage and Internet marketing intensity, which in turn leads to international market growth, in terms of increased sales from new customers in new countries, new customers in existing countries and from existing customers.