Aktuelle Publikationen

November 2023

Langevin Cooling for Unsupervised Domain Translation

Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Shinichi Nakajima

In this paper, we show that many of such unsuccessful samples in image-to-image translation lie at the fringe—relatively low-density areas of data distribution, where the DNN was not trained very well. To tackle this problem we propose to perform...

November 2023

Towards automated digital building model generation from floorplans and on-site images

Niklas Gard, Aleixo Cambeiro Barreiro

We propose a system to automatically generate enriched digital models from this data, consisting of two AI modules: one for 3D model reconstruction from 2D plans and one for 6D localization of images taken within a building in the corresponding...

November 2023

Characterization of C-Band Coherent Receiver Front-ends for Transmission Systems beyond S-C-L-Band

Robert Emmerich, Colja Schubert, Carsten Schmidt-Langhorst, Ronald Freund

Fraunhofer HHI Researchers investigate in this publication a cost-efficient capacity upgrade of optical transmission systems by the reuse of already deployed single mode fiber. This is enabled by the benefits of other transmission bands, to...

Oktober 2023

Design and Fabrication of Crossing-free Waveguide Routing Networks using a Multi-layer Polymer-based Photonic Integration Platform

Madeleine Weigel, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David de Felipe Mesquida, Martin Kresse, Norbert Keil, Hauke Conradi, Anja Scheu, Jakob Reck, Klara Mihov

A novel 16x4 crossing-free waveguide routing network on four layers of polymer-based stacked waveguides is presented. The design and fabricated device combine in-plane passive waveguide structures with vertical multimode interference couplers to...

Oktober 2023

Pre-Training with Fractal Images Facilitates Learned Image Quality Estimation

Malte Silbernagel, Thomas Wiegand, Peter Eisert, Sebastian Bosse

Current image quality estimation relies on data-driven approaches, however the scarcity of annotated data poses a bottleneck. This paper introduces a novel pre-training approach utilizing synthetic fractal images. The proposed method is tested on...

Oktober 2023

Private and Secure Over-the-Air Multi-Party Communication

Jan Jonas Brune, Slawomir Stanczak, Igor Bjelakovic, Matthias Frey, Felix Klement, Stefan Katzenbeisser

Over-the-Air Multi-Party Communication for scalable, private, secure and dependable data aggregation: This novel approach combines lattice coding, Over-the-Air computation and secure Multi-Party Communication to confidentially aggregate analog...

Oktober 2023

A Differentiable Gaussian Prototype Layer for Explainable Fruit Segmentation

Michael Gerstenberger, Peter Eisert, Sebastian Bosse, Steffen Maaß

We introduce a GMM Layer for gradient-based prototype learning. It is used to cluster feature vectors by computing their probabilities for each gaussian and using the soft cluster assignment for prediction. Hence prototypical image regions can be...

September 2023

From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation

Reduan Achtibat, Thomas Wiegand, Sebastian Bosse, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer, Ilona Eisenbraun

We introduce the Concept Relevance Propagation (CRP) approach, which combines the local and global perspectives and thus allows answering both the ‘where’ and ‘what’ questions for individual predictions. We demonstrate the capability of our...

September 2023

When it comes to Earth observations in AI for disaster risk reduction, is it feast or famine? A topical review

Monique Kuglitsch, Jackie Ma, Arif Albayrak, Allison Craddock, Andrea Toreti, Elena Xoplaki, Jürg Lüterbacher, Paula Padrino Vilela, Rui Kotani, Dominique Berod, Jon Cox

Given the number of in situ and remote (e.g. radiosonde/satellite) monitoring devices, there is a common perception that there are no limits to the availability of EO for immediate use in such AI-based models. However, a mere fraction of EO is...

September 2023

Hybrid semantic clustering of 3D point clouds in construction

Marcus Zepp

In this work, we present an artificial intelligence (AI)-based semantic segmentation approach for three-dimensional (3D) point clouds which were generated from 2D images with a structure from motion (SfM) pipeline. We utilize state-of-the-art...

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