Fakultät Elektrotechnik und Wirtschaftsingenieurwesen
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In order to provide more transparency on convolutional neural networks (CNN) for education and research purposes this work has three main objectives:
• Create CNN models based on two different architectures, which classify magnetic resonance images of the brain into normal and abnormal
• Investigate these models by applying state of the art visualization techniques. For this purpose, a simple accessible Application Interface (API) for Keras sequential models will be developed.
• Describe the quality of the models based on the visualizations and compare their overall classification to the human classification procedure.