Clustering

Machine Learning

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.

Accoustic Source Characterisation

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.

Clustering-Based Quantisation for PDE-Based Image Compression

Optimal known pixel data for inpainting in compression codecs based on partial differential equations is real-valued and thereby expensive to store. Thus, quantisation is required for efficient encoding. In this paper, we interpret the quantisation …

Sparse $l_{1}$ Regularisation of Matrix Valued Models for Acoustic Source Characterisation

We present a strategy for the recovery of a sparse solution of a common problem in acoustic engineering, which is the reconstruction of sound source levels and locations applying microphone array measurements. The considered task bears similarities …

Sparse $l_{1}$ Regularisation of Matrix Valued Models for Acoustic Source Characterisation

Poster presentation

Highly Robust Clustering of GPS Driver Data for Energy Efficient Driving Style Modelling

This paper presents a novel approach to distinguish driving styles with respect to their energy efficiency. A distinct property of our method is that it relies exclusively on Global Positioning System (GPS) logs of drivers. This setting is highly …

Efficient Co-domain Quantisation for PDE-based Image Compression

Poster presentation

Efficient Co-domain Quantisation for PDE-based Image Compression

Finding optimal data for inpainting is a key problem for image compression with partial differential equations (PDEs). Not only the location of important pixels but also their values should optimise the compression quality. The position of such …