Recent publications

Auditing AI systems is a complex endeavour since multiple aspects have to be considered along the AI lifecycle that require multi-disciplinary approaches. AI audit methods and tools are in many cases subject of research and not practically...

We fabricate low-loss AlGaAs Bragg-reflection waveguides for the creation of C-band photon pairs via parametric down-conversion. These photon pairs are used in a hybrid on-chip time-bin entanglement scheme.

This book takes next steps towards a broader vision for explainable AI in moving beyond explaining classifiers, to include explaining other kinds of models (e.g., unsupervised and reinforcement learning models) via a diverse array of XAI...

In this chapter, we review our recently proposed "neuralization-propagation" (NEON) approach for bringing XAI to workhorses of unsupervised learning. NEON first converts the unsupervised model into a functionally equivalent neural network so...

In this chapter, we develop and describe a novel quantization paradigm for DNNs: Our method leverages concepts of explainable AI (XAI) and concepts of information theory: Instead of assigning weight values based on their distances to the...

In this paper, we propose a detailed generic reference plane model for performance evaluation and system validation of radio channel sounders. It allows to abstractly describe a broad variety of channel sounder implementations and architectures...

The mmWave band offers high bandwidths, but drawbacks such as limited range and susceptibility to blockage remain a challenge. In this paper, we take off-the-shelf mmWave devices in the 60 GHz band and combine them with custom lenses. As a...

This paper proposes a novel approach for coherent detection with double-side vertically illuminated photodetectors. Signal and local oscillator are injected collinearly from opposite sides of the photodetector chip. The concept inherently...

We theoretically investigate and demonstrate coherent detection with double-side vertically illuminated photodiodes by injecting signal and local oscillator collinearly from opposite sides of the photodetector chip. A first proof of concept for...

An all-photonic THz-receiver PIC comprising an on-chip frequency stabilization scheme and a novel InP-based photoconductive antenna is presented in this paper. Characterization of the key photonic building blocks shows the functionality of the...

To keep up with the rapid growth in global traffic, next-generation optical communication networks aim to vastly increase capacity by exploiting a larger optical transmission window covering the S-C-L-band. To reuse current commercially available...

We present a solution for Accurate and temporally consistent modeling of human performances from video sequences. In detail, we derive parameters of a sequence of body models, representing shape and motion of a person, including jaw poses, facial...

The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision. In...

We present a multi-object 6D detection and tracking pipeline for potentially similar and non-textured objects. The combination of a convolutional neural network for object classification and rough pose estimation with a local pose refinement and...

Neural Network Coding and Representation (NNR) is the first international standard for efficient compression of neural networks. The NNR standard contains quantization and an arithmetic coding scheme as core encoding and decoding technologies, as...

This paper adresses the problem of structural damage detection in transmission towers, addressing these two common challenges: (i) the lack of freely available training data and the difficulty to collect it; (ii) fuzzy boundaries of what...

We present photomixers made of InGaAs:Fe as broadband receivers in optoelectronic cw THz systems. The improved resistivity and carrier lifetime of InGaAs:Fe enable us to measure a bandwidth of 4.5 THz with a peak dynamic range of 112 dB. When...

We present a publicly available dataset collection to open the problem of data-driven QoT estimation to the ML community. The dataset collection allows comparing various solutions presented by different research groups. Furthermore, we propose...

This article investigates the usefulness of Explainable Artificial Intelligence (XAI) methods to increase transparency in automated clinical gait classification based on time series. For this purpose, predictions of state-of-the-art...

Contemporary learning models for computer vision are typically trained on very large (benchmark) datasets with millions of samples. These may, however, contain biases, artifacts, or errors that have gone unnoticed and are exploitable by the...

We compare a state-of-the-art terahertz (THz) time domain spectroscopy (TDS) system and a novel optoelectronic frequency domain spectroscopy (FDS) system with respect to their performance in layer thickness measurements on dielectric samples....

Being self-represented through an avatar increases embodiment and the feeling of presence in virtual reality. Nevertheless, currently users in VR are typically represented only by their hands, as not enough tracking data is available for full...

In this work, we enhance a professional end-to-end volumetric video production pipeline to achieve high-fidelity human body reconstruction using only passive cameras.We introduce and optimize deep learning based multi-view stereo networks for...

Safe operation of driver assistance systems remains a challenge, especially at higher speeds. It requires sensor technology that is capable of detecting surrounding conditions even at large distances. LiDAR technology is a cornerstone of this...

We demonstrate InP based PICs with MMIs and waveguide integrated avalanche photodiodes (APD). We investigate these devices regarding their DC and RF linearity characteristics and find a high bandwidth beyond 20 GHz and a dynamic range of 30 dB...

It is common to observe signi?cant disagreements amongst the quality predictions of these VQMs for the same video sequence. Herein, a measure for quantifying the disagreement between VQMs is proposed. We propose a disagreement measure that...

The H2020 METRO-HAUL European project has architected a latency-aware, cost-effective, agile, and programmable optical metro network. This includes the design of semidisaggregated metro nodes with compute and storage capabilities, which interface...

We propose a secure aggregation algorithm that allows proprietary-owned domains, hosting statistically different datasets, train and operate ML models in a Horizontally Federated Learning fashion. The obtained results show a compelling test...

We present a novel framework that enables vendors and operators, with partial access to operational and monitoring features of a service, to collaboratively develop a ML-assisted solution without revealing any business-critical raw data to each...