Computer Graphics
TU Braunschweig

Physical Parameter Estimation from Images

Abstract

The goal of this project is to develop fast image-based measurement methods for optical properties, which would help to close feedback loops in adaptive manufacturing.

The introduction of novel production techniques for integrated optical components demands an increasing amount of quality control and inline feedback. Our focus in this project is the combination of fast optical measurement techniques and physics-based simulations to achieve fast and accurate feedback of physical parameters as close to the machine tool as possible.

The research on this topic is done in collaboration with the PhoenixD Cluster of Excellence. We work closely with expert researchers from other disciplines under the Task Group F2: Expert Systems for Quality Control.

Publications


Marc-André Dittrich, Bodo Rosenhahn, Marcus Magnor, Berend Denkena, Talash Malek, Marco Munderloh, Marc Kassubeck:
Dreaming Neural Networks for Adaptive Polishing
in Proc. Int. Conf. European Society for Precision Engineering and Nanotechnology (euspen), June 2020.


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