Martin Drauschke

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Though the replacement of European bees by Africanized honey bees in tropical America has attracted considerable attention, little is known about the temporal changes in morphological and genetic characteristics in these bee populations. We examined the changes in the morphometric and genetic profiles of an Africanized honey bee population collected near(More)
The paper addresses the problem of feature selection during classification of image regions within the context of interpreting images showing highly structured objects such as buildings. We present a feature selection scheme that is connected with the classification framework Adaboost, cf. (Schapire and Singer, 1999). We constricted our weak learners on(More)
This paper addresses the problem of feature selection within classification processes. We present a comparison of a feature subset selection with respect to two boosting methods, Adaboost and ADTboost. In our evaluation, we have focused on three different criteria: the classification error and the efficiency of the process depending on the number of most(More)
The conservation and sustainable utilization of global biodiversity necessitates the mapping and assessment of the current status and the risk of loss of biodiversity as well as the continual monitoring of biodiversity. These demands in turn require the reliable identification and comparison of animal and plant species or even subspecies. We have developed(More)
In our contribution, we improve image segmentation by integrating depth information from multi-view analysis. We assume the object surface in each region can be represented by a low order polynomial, and estimate the best fitting parameters of a plane using those points of the point cloud, which are mapped to the specific region. We can merge adjacent image(More)
Texture is one of the most important features for object detection and recognition. In many applications, it is derived from the responses of texture filters. In this paper, we evaluate the potential of seven texture filter banks for the pixel-based classification of terrestrial facade images. Particularly, we analyze features from Gabor, Haar, Root Filter(More)