Aktuelle Publikationen

We propose two algorithms that use both models and datasets to estimate angular power spectra from channel covariance matrices in massive MIMO systems. The first algorithm is an iterative fixed-point method that solves a hierarchical problem. It uses model knowledge to narrow down candidate angular power spectra to a set that is consistent with a measured covariance matrix. Then, from this set, the algorithm selects the angular power spectrum with minimum distance to its expected value with respect to a Hilbertian metric learned from data. The second algorithm solves an alternative optimization problem with a single application of a solver for nonnegative least squares programs. By fusing information obtained from datasets and models, both algorithms can outperform existing approaches based on models, and they are also robust against environmental changes and small datasets.

Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV- 2 pandemic. In this work we propose an approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies.

We present photoconductive terahertz (THz) emitters based on rhodium (Rh) doped InGaAs for time-domain spectroscopy (TDS). The emitters feature a record high THz power of 637 µW. In combination with InGaAs:Rh receivers, a 6.5 THz bandwidth and a record peak dynamic range of 111 dB can be achieved. These improvements enable layer thickness measurement systems with unprecedented resolution and accuracy.

Optical feedback has an impact on the tunability of lasers. We created a model of a tunable distributed Bragg reflector (DBR) laser describing the effect of optical feedback from a constant reflector distance on the wavelength tuning. Theoretical and experimental results are in good agreement. A further discussion of the model sheds light on design rules to reduce the effect of optical feedback on the tuning behavior. We introduced a new parameter called mode loss difference (MLD) as a metric for the feedback tolerance of the tuning behavior. A large MLD indicates higher tolerance of the laser to cavity length variations.

A morphed face image is a fusion of two face images and represents biometrics of two different subjects. Embedded in an official document, it can cause immense damage, since both subjects can claim its ownership and thus share an identity. In this paper, we propose and compare different neural network training schemes based on alternations of training data to obtain accurate and robust detectors for such kind of fraud. In addition, we use layer-wise relevance propagation (LRP) to analyze the differently trained networks in depth.

Federated Learning (FL) is currently the most widely adopted framework for collaborative training of (deep) machine learning models under privacy constraints. However, FL yields suboptimal results if the local clients’ data distributions diverge. The proposed Clustered FL approach tackles the problem by identifying diverging clients and grouping them into separate clusters.

We present an end-to-end pipeline for the creation of high-quality animatable volumetric video content of human performances. Going beyond the application of free-viewpoint volumetric video, we allow re-animation of an actor’s performance through (i) the enrichment of the captured data with semantics and animation properties and (ii) hybrid geometry- and video-based animation combined with neural infilling.

Coherent comb lasers may serve as a source for multiwavelength modulators in short reach transmission, or for phase controlled OFDM channels in long reach. We explore and compare quantum dot (QD) and quantum well (QW) lasers with more than 33 channels in the DWDM 50 GHz grid, thus enabling > 1 Tb/s optical transmission. In addition, the mode-locked devices can be applied as pulse sources with < 500 fs pulses by using a simple SMF.

Photo-realistic modeling and rendering of humans is extremely important for VR environments. While purely computer graphics modeling can achieve highly realistic human models, achieving real photo-realism with these models is computationally extremely expensive. Therefore, we enrich volumetric video with semantics and animation properties to make photo-realistic volumetric video animatable.

We determine the absorption and scattering coefficients of cholesteatoma and bone. In the near-UV and visual spectrum, clear differences exist between both tissues. These differences reveal the future possibility to detect and identify, automatically or semi-automatically, cholesteatoma tissue for active treatment decisions during image-guided surgery leading to a better surgical outcome.