Aktuelle Publikationen

Future networks aim for higher data rates through cell densification, leading to frequent handovers and increased signaling overhead for moving user equipment (UE). This paper presents an optimization scheme using predicted channel state...

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.

This paper investigates efficient scheduling algorithms for coexistence scenarios of devices with different quality of service requirements, such as URLLC and eMBB. It proposes a low-complexity algorithm that outperforms current methods, with...

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...

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...

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 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...

Our method builds on existing state-of-the-art 3D GAN inversion techniques to allow for consistent and simultaneous inversion of multiple views of the same subject. We employ a multi-latent extension to handle inconsistencies present in dynamic...

This study investigates the effectiveness of neural network architectures in hyperspectral image demosaicing. We introduce a range of network models and modifications, and compare them with classical interpolation methods and existing reference...