Pixel-wise Segmentation of Street with Neural Networks

Martin Thoma; Marvin Teichmann; Sebastian Bittel; Vitali Kaiser

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Pixel-wise Segmentation of Street with Neural Networks

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arxiv 1511.00513 v1 pith:U7LDHTCE submitted 2015-11-02 cs.CV

Sebastian Bittel , Vitali Kaiser , Marvin Teichmann , Martin Thoma This is my paper · ORCID

classification cs.CV

keywords neuralnetworknetworkspixel-wisesegmentationstreetaccuracyachieved

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abstract

Pixel-wise street segmentation of photographs taken from a drivers perspective is important for self-driving cars and can also support other object recognition tasks. A framework called SST was developed to examine the accuracy and execution time of different neural networks. The best neural network achieved an $F_1$-score of 89.5% with a simple feedforward neural network which trained to solve a regression task.

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