Recent publications

We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. We represent surfaces as triangle meshes and build a differentiable rendering pipeline around triangle...

The goal of pollution forecasting models is to allow the prediction and control of the air quality. While such deep learning models were deemed for a long time as black boxes, recent advances in eXplainable AI (XAI) allow to look through the...

Due to the rising threat of deepfakes to security and privacy, it is most important to develop robust and reliable detectors. In this paper, we examine the need for high-quality samples in the training datasets of such detectors. Accordingly, we...

Multimodal user interfaces promise natural and intuitive human–machine interactions. However, is the extra effort for the development of a complex multisensor system justified, or can users also be satisfied with only one input modality? This...

While the evaluation of explanations is an important step towards trustworthy models, it needs to be done carefully, and the employed metrics need to be well-understood. Specifically model randomization testing is often overestimated and regarded...

Applying traditional post-hoc attribution methods to segmentation or object detection predictors offers only limited insights, as the obtained feature attribution maps at input level typically resemble the models' predicted segmentation mask or...

State-of-the-art machine learning models often learn spurious correlations embedded in the training data. This poses risks when deploying these models for high-stake decision-making, such as in medical applications like skin cancer detection. To...

Explainable AI (XAI) is a rapidly evolving field that aims to improve transparency and trustworthiness of AI systems to humans. One of the unsolved challenges in XAI is estimating the performance of these explanation methods for neural networks,...

Explainable Artificial Intelligence (XAI) is an emerging research field bringing transparency to highly complex and opaque machine learning (ML) models. This paper offers a comprehensive overview over techniques that apply XAI practically to...

Sydnone methides represent an almost unknown class of mesoionic compounds which possess exocyclic carbon substituents instead of oxygen (sydnones) or nitrogen (sydnone imines) in the 5-position of a 1,2,3-oxadiazolium ring. Unsubstituted...

Recent work in XAI for eye tracking data has evaluated the suitability of feature attribution methods to explain the output of deep neural sequence models for the task of oculomotric biometric identification. In this work, we employ established...

Researchers from NICT, University of L’Aquila, Finisar, Prysmian and Nokia Bell Lab demonstrate a 2-line side 15-mode spatial division multiplexing network node based on fifteen 2×2 wavelength cross-connects to direct up to six 5 Tb/s, 15-mode,...

In this work we investigate cell damage in whole slice images of the epidermis. A common way for pathologists to annotate a score, characterising the degree of damage for these samples, is the ratio between healthy and unhealthy nuclei. The...

In this study, we pair traditional machine learning with physical optics to obtain explicit and differentiable data models. We demonstrate how such data models can be constructed for image data and used to control downstream machine learning...

In this work, we experimentally and numerically compare cyclic shifted constant-amplitude zero-autocorrelation (CAZAC) training sequences (TS) with different number of repetitions, sequence lengths and scalings for channel estimation in an...

We implemented an all-optical C-to-S band wavelength converter based on low-complexity SOI strip waveguides. Its bandwidth was optimized and crosstalk issues were modeled numerically. These devices were experimentally evaluated to have a...

For the first time, channel measurements at 300 GHz from various environments and different measurement systems are jointly analyzed and published.

The Berlin V2X dataset offers high-resolution GPS-located wireless measurements across diverse urban environments in the city of Berlin for both cellular and sidelink radio access technologies, including information on the physical layer,...

A novel polymer-based 1x4 vertical multimode interference (MMI) coupler for 3D photonics is presented. It connects four vertically stacked waveguide layers with a spacing of 21.6 µm. The functionality is demonstrated on a fabricated device.

Existing challenges in surgical education (See one, do one, teach one) as well as the COVID-19 pandemic make it necessary to develop new ways for surgical training. This work describes the implementation of a scalable remote solution called...