Aktuelle Publikationen

For time series data, where the input itself is often not interpretable, dedicated XAI research is scarce. In this work, we put forward a virtual inspection layer for transforming the time series to an interpretable representation and allows to...

This paper introduces a new concept and outlines the implementation of an AR application designed for mobile devices. It can visualize real-time environmental data from various Open Data platforms. The scientific contribution lies in diverse...

We present a fiber-pigtailed hybrid photonic circuit comprising nonlinear waveguides for photon-pair generation and a polymer interposer reaching 68 dB of pump suppression and photon separation based on a polarizing beam splitter with > 25 dB...

Sub-THz communication, vital for 6G, requires densification and multi-connectivity to overcome signal blockage. Efficient beam and user scheduling are crucial. We propose a low-complexity scheduling scheme using machine learning (ML), employing a...

This paper addresses the massive MIMO unsourced random access problem in quasi-static Rayleigh fading. Our proposed coding scheme combines an outer LDPC code with an inner SPARC code, integrating channel estimation, single-user decoding, and...

We propose a novel representation of virtual humans for highly realistic real-time animation and rendering in 3D applications. We learn pose dependent appearance and geometry from highly accurate dynamic mesh sequences obtained from...

We utilized an EEG dataset of steady-state visual evoked potentials in which participants were presented with human face images of different stylization levels. Assessing neuronal responses, we found a non-linear relationship between SSVEP...

AI has proven effective in classifying skin cancers using dermoscopy images. However, clinical application is limited when algorithms are not well-trained, or there is a lack of clinical context (e.g., medical history). The increasing use of...

This article advances the theoretical foundations of user-centric cell-free massive MIMO networks. In particular, by means of a novel UL-DL duality principle for fading channels, it settles the optimality of the recently developed “team MMSE”...

We present iV2V and iV2i+, two machine-learning datasets for industrial wireless communication. The datasets cover sidelink and cellular communication involving autonomous robots together with localization and sensing data, which can be used to...

Traditional signal processing methods often fall short compared to data-driven approaches in a signal separation problem that involves co-channel signals, where the energy content of the interference component overlaps with the transmitted signal...

This paper compares the sub-THz radio channel characteristics at 158 GHz and 300 GHz in a shopping mall scenario by extracting three different path loss models and various channel parameters.

We present a novel method ensuring the right reasons on the concept level by reducing the model's sensitivity towards biases through the gradient. When modeling biases via Concept Activation Vectors, we highlight the importance of choosing robust...

Solid-state optical beam-steering utilizing polymer waveguides as edge emitters to form optical phased arrays (OPAs) with aperiodic spacing for operation at 1550 nm is demonstrated for the first time. Power consumption of 1.28 mW/? per channel is...

This work integrates an evanescent Bragg grating sensor into a polymer waveguide with microchannels. The sensor, built with epoxide-based polymers, is characterized through chemical applications. Temperature sensitivity is demonstrated (-47.75...

We validate experimentally the claim that, in sub-THz mobile access networks, single-carrier or low-number-of-subcarriers modulations are very attractive competitors to the dramatically more complex and energy-inefficient traditional...

We present a novel approach combining two calibrated multispectral real-time capable snapshot cameras, covering different spectral ranges, into a stereo-system. Therefore, a hyperspectral data-cube can be continuously captured. The combined use...

We propose a method for automatic prevention of ghosting artifacts based on a pixel-wise alignment during morph generation. We evaluate our proposed method on state-of-the-art detectors and show that our morphs are harder to detect, particularly,...

We propose a generative deep learning network for texture map super-resolution using a differentiable renderer and calibrated reference images. Combining a super-resolution generative adversarial network (GAN) with differentiable rendering, we...

We introduce a novel NeRF-based framework for pose-dependent rendering of human performances where the radiance field is warped around an SMPL body mesh, thereby creating a new surface-aligned representation. Our representation can be animated...