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A Comparison of Classifiers for Prescreening of Honeybee Brood Cells

Knauer, Uwe ; Zautke, Fred ; Bienefeld, Kaspar ; Meffert, Beate

The 5th International Conference on Computer Vision Systems, 2007
Bielefeld, 21. - 24. März 2007

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Abstract:
We report on an image classification task originated from the video observation of beehives. Biologists desire to have an automatic support to identify so called hygienic bees. For this it is important to know which brood cells are in a stadium of initial opening. To find these cells a prescreening process is necessary which classifies three types of cells. To solve this decision problem a number of classification techniques are evaluated. ROC-analysis for the given problem shows that the SVM classifier with RBF kernel outperforms linear discrimance analysis, decision trees, boosted classifiers, and other kernel functions.


Keywords: Evaluation, Classification, Honeybee, Detection, Varroa
Institution: Faculty of Technology, Research Groups in Informatics
DDC classification: Data processing, computer science, computer systems

Suggested Citation:
Knauer, Uwe ; Zautke, Fred ; Bienefeld, Kaspar ; Meffert, Beate  (2007)  A Comparison of Classifiers for Prescreening of Honeybee Brood Cells. The 5th International Conference on Computer Vision Systems, 2007


URL: http://biecoll.ub.uni-bielefeld.de/volltexte/2007/31



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