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2006

Towards Automatic Segmentation of Serial High-Resolution Images

13 years 5 months ago
Towards Automatic Segmentation of Serial High-Resolution Images
Developing barley grains are to be visualised by a 4-D model, in which spatiotemporal experimental data can be integrated. The most crucial task lies in the automation of the extensive segmentation procedure. Because of constraints like incomplete a-priori expert knowledge and the complexity of this specific segmentation task, learning techniques like Artificial Neural Networks (ANN ) yield promising solutions. In this work we present our first good segmentation results. Two different supervised trained ANN classifiers were applied, on one hand, the wellestablished borderline-learning Multiple-Layer Perceptron (MLP) and on the other hand, the prototype-based Supervised Relevance Neural Gas (SRNG). While so far segmentation was mainly achieved using manual tools, now almost automatic segmentation becomes more feasible.
Cornelia Brüß, Marc Strickert, Udo Seif
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where BILDMED
Authors Cornelia Brüß, Marc Strickert, Udo Seiffert
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