Using fully convolutional neural networks for object detection in robot welding applications
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2017-08-28
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en
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In this thesis we have tried to use deep convolutional neural networks in a automated welding application. This application was the instant robot programming system from Exner. The network used was the fully convolutional U-net architecture because it performed well with few training examples, accepts inputs from most sizes and separates on a pixel level. The network was trained on a in this thesis created training set and able to separate most inputs correctly with an average recall rate of 86,80%.
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Faculteit der Sociale Wetenschappen