A computer vision system for the recognition of trees in aerial photographs

Increasing problems of forest damage in Central Europe set the demand for an appropriate forest damage assessment tool. The Vision Expert System (VES) is presented which is capable of finding trees in color infrared aerial photographs. Concept and architecture of VES are discussed briefly. The system is applied to a multisource test data set. The processing of this multisource data set leads to a multiple interpretation result for one scene. An integration of these results will provide a better scene description by the vision system. This is achieved by an implementation of Steven's correlation algorithm

Neural Network `Surgery': Transplantation of Hidden Units

We present a novel method to combine the knowledge of several neural networks by replacement of hidden units. Applying neural networks to digital image analysis, the underlying spatial structure of the image can be propagated into the network and used to visualize its weights (WV-diagrams). This visualization tool helps to interpret the behaviour of hidden units. We notice a process of specialization of certain hidden units, while others remain apparently useless. These units are cut out of one network and replaced by units taken from other networks trained for the same task using different parameters. We achieve better prediction accuracies for the new, combined network than for any of the two original ones. This constitutes a special kind of information fusion in image understanding