Andreas Schwenk

Technische Hochschule Köln | FH Köln · Faculty of Information, Media and Electrical Engineering

Computer vision abilities of autonomous systems have a significant computational demand on the underlying hardware. We research on methods to reduce the amount of data provided to Artificial Neural Networks (ANN)-based image classification. We consider transformation techniques, as many visual sensors inherently provide hardware components for the...

Making reliable and comprehensible decisions in the context of renewable energy requires complex software solutions. Based on previous work that specifies the Cross Energy Management Programming Language (CEMPL), we present a new web-based tool chain to map real-world objectives and constraints to a set of formalized problem descriptions that is so...

We address the modeling and optimization of the coupling of energy sectors. Given a network infrastructure in form of a graph G = (V,E) that consists of a priori unconnected components, the objective is to synthesize an optimal set of parameterized energy converters and energy storages. This enables cross-sectoral interconnection and facilitates to...

The extensive involvement of energy conversion and storage technologies is becoming increasingly important in the context of energy transition. A sufficient modeling and simulation of large-scale and coherent cross-energy systems is essential to enable decision makers to put the right course. This process implies growing complexity in terms of phys...

We propose in this paper a novel visual computing approach for the automatic perception of chess gaming states, where a standard chessboard with original chess pieces is used. Our image analysis algorithm uses only grayscale images captured from a single mobile camera for interactive gaming under natural environmental conditions. On the one hand, w...

Vision Sensors for Cloud Applications have to drastically reduce the amount of image data that is transferred and stored. Due to the fact that such sensors are mostly bulk products, they must be optimized according to their performance, price, size and energy consumption. We present an approach for video compression that fulfills these needs by usi...

A new bio–inspired computer architecture (General Purpose Neural Processor), that is based on large clusters of artificial neurons, is proposed. We postulate a lightweight programming language (DPLNA) and design, as well as implement an appropriate compiler. The main focus of this thesis is on high parallelization and the efficient mapping of conve...