Search Results for author: Sebastian Zambal

Found 4 papers, 3 papers with code

BlendTorch: A Real-Time, Adaptive Domain Randomization Library

1 code implementation6 Oct 2020 Christoph Heindl, Lukas Brunner, Sebastian Zambal, Josef Scharinger

Solving complex computer vision tasks by deep learning techniques relies on large amounts of (supervised) image data, typically unavailable in industrial environments.

object-detection Object Detection

End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data

no code implementations11 Oct 2019 Sebastian Zambal, Christoph Heindl, Christian Eitzinger, Josef Scharinger

This leads to an appealing method that scales well with new defect types and measurement devices and requires little real world data for training.

Defect Detection Image Segmentation +2

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