Comparing Three Machine Learning Techniques for Building Extraction from a Digital Surface Model

Machine Learning techniques for applied Information Extraction

Advanced Machine Learning Techniques for Digital Mammography

A common thinking about the science is that every possible achievement can be pursued, provided that we have time and funds available for that purpose. On top of all this, recent technological achievements have carried this thinking to extremes, due to the speed of technological change sweeping through the world, which led to new momentous discoveries. Hence for researchers themselves there is ...

An Approach to Building Extraction from Digital Surface Models

Motivated by the test data sets of ISPRS WG III on image understanding we investigate the feasibility of building extraction using high resolutionDigital Surface Models DSM as input data which do not only contain information about the topographic surface like Digital Elevation Models DEM but also information about the buildings The steps of the proposed procedure increasingly use explicit domai...

Building footprint extraction from Digital Surface Models using Neural Networks

Two-dimensional building footprints are a basis for many applications: from cartography to three-dimensional building models generation. Although, many methodologies have been proposed for building footprint extraction, this topic remains an open research area. Neural networks are able to model the complex relationships between the multivariate input vector and the target vector. Based on these...

Integrated Method of Building Extraction from Digital Surface Model and Imagery

In urban GIS and management, Digital surface model (DSM) can be used for generating object models. The preliminary step is to segment the interesting areas. In this paper, we present an integrated method of building extraction using transform from DSM to normal angles and watershed segmentation to the gradient of DSM. To remove the effect of the terrain shape to building detection, we firstly d...