Clustering

I have used machine learning techniques in various projects. Our most successful applications were in the context of quantizing colour values for optimized inpainting and in accoustic source characterizations. Source Code The source code for clustering methods used for quantizing optimal masks can be found here. The source code for the accoustic source characterization is here.

Let us consider a microphone array comprising $n$ microphones at known locations (see figure above). These microphones register the sound that is emitted by a number of sources with unknown locations. The characterization of these acoustic sources requires the estimation of their location and strength. The propagation of sound from a source position $x$ to a receiver at position $y$ can be modelled by a Green’s function. In the following we assume that the source is always a monopole.

Optimal known pixel data for inpainting in compression codecs based on partial differential equations is real-valued and thereby …

We present a strategy for the recovery of a sparse solution of a common problem in acoustic engineering, which is the reconstruction of …

Poster presentation

This paper presents a novel approach to distinguish driving styles with respect to their energy efficiency. A distinct property of our …

Poster presentation

Finding optimal data for inpainting is a key problem for image compression with partial differential equations (PDEs). Not only the …