Recent publications

We demonstrate a fully packaged photodetector module based on surface-illuminated modified uni-traveling-carrier (MUTC) photodiode (PD) and investigate its DC and RF characteristics. It has a very a low dark current below 2 nA at the operational...

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...

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...

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...

This paper puts forward first benchmarking results for the PTB-XL dataset, covering a variety of tasks from different ECG statement prediction tasks over age and gender prediction to signal quality assessment. We find that convolutional neural...

Federated Learning comes at the cost of a significant communication overhead during training. In this work, we propose Sparse Ternary Compression (STC), a new compression framework that is specifically designed to meet the requirements of the...

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...

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...

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....

Polarization division multiplexing doubles the transmission capacity of optical communication systems. For such systems, splitters separating the TE from the TM mode are indispensable components. We design and manufacture an integrated InP-based...

Electrocardiography (ECG) is increasingly supported by algorithms based on machine learning. We put forward PTB-XL, the to-date largest freely accessible clinical 12-lead ECG-waveform dataset comprising 21837 records from 18885 patients of 10...

AI solutions have not by large entered routine dental practice, mainly due to (1) limited data availability, accessibility, structure and comprehensiveness, (2) lacking methodological rigor and standards in their development, (3) and practical...

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...

This work shows the application of explainable AI (XIA) methods to resolve common challenges encountered in deep learning-based digital histopathology analyses. We investigate three types of biases and show that XAI techniques are helpful and...

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...

Deep models are also being increasingly applied in distributed settings, where the data are separated by limited communication channels and privacy constraints. To address the challenges, a wide range of training and evaluation schemes have been...

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,...

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...

This paper presents DeepCABAC, a universal compression algorithm for deep neural networks (DNNs) that through its adaptive, context-based rate modeling, allows an optimal quantization and coding of parameters. It compresses DNNs up to 5% of...

Inferring the properties of protein from its amino acid sequence is a key problem in bioinformatics. We put forward UDSMProt, a universal deep sequence model that is pretrained on a language modeling task and finetuned on protein classification...