Aktuelle Publikationen

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...


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...


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

Unsupervised learning of style-aware facial animation from real acting performances

Wolfgang Paier, Peter Eisert, Anna Hilsmann

This paper presents a novel approach for text/speech-driven animation of a photo-realistic head model based on blend-shape geometry, dynamic textures, and neural rendering. Training a VAE for geometry and texture yields a parametric model for...


September 2023

Video-Driven Animation of Neural Head Avatars

Wolfgang Paier, Peter Eisert, Anna Hilsmann, Paul Hinzer

We present a new approach for video-driven animation of high-quality neural 3D head models, addressing the challenge of person-independent animation from video input.In order to achieve person-independent animation from video input, we introduce...


September 2023

From Multispectral-Stereo to Intraoperative Hyperspectral Imaging: a Feasibility Study

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Philipp Arens, Benjamin Kossack, Brigitta Globke, Jost Triller

Spectral imaging allows to analyze optical tissue properties that are invisible to the naked eye. We present a novel approach using two multispectral snapshot cameras covering different spectral ranges as a stereo-system. The proposed method...


September 2023

Automatic Registration of Anatomical Structures of Stereo-Endoscopic Point Clouds

Sophie Beckmann, Peter Eisert, Anna Hilsmann, Jean-Claude Rosenthal, Eric Wisotzky

In this paper, we present an analysis and registration pipeline for confined point clouds acquired by stereo endoscopes into a fused representation. For a coarse registration, TEASER is applied, while a refinement is conducted utilizing...


September 2023

Surgical Phase Recognition for different hospitals

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Sophie Beckmann, Lasse Renz-Kiefel, sebastian Lünse, Rene Mantke

Surgical phase recognition is an important aspect of surgical workflow analysis, as it allows an automatic analysis of the performance and efficiency of surgical procedures. A big challenge for training a neural network for surgical phase...


September 2023

3D Hyperspectral Light-Field Imaging: a first intraoperative implementation

Eric Wisotzky, Peter Eisert, Anna Hilsmann

Hyperspectral imaging is an emerging technology that has gained significant attention in the medical field due to its ability to provide precise and accurate imaging of biological tissues. The current methods of hyperspectral imaging, such as...


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...


September 2023

FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning

Felix Sattler, Wojciech Samek, Roman Rischke, Tim Korjakow

In this work, we propose FEDAUX, an extension to Federated Distillation, which, under the same set of assumptions, drastically improves the performance by deriving maximum utility from the unlabeled auxiliary data. Our proposed method achieves...


August 2023

Eight-channel SiNx microring–resonator based photonic biosensor for label-free fluid analysis in the optical C-band

Jakob Reck, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David de Felipe Mesquida, Martin Kresse, Hauke Conradi, Tianwen Qian, Cafercan Yilmaz, Madeleine Weigel, Klara Mihov, Christina Hoffmann, Peter Hoffmann, Vera Froese, Ulrich Kertzscher, Kristina Mykhailiuk, Julia Michaelis, Wilfired Weigel, Sören Scholand, Hans-Jürgen Heupke

A lab-on-a-chip multichannel sensing platform for biomedical analysis based on optical silicon nitride (SiNx) microring-resonators (MRR) was established. The resonators were surface functionalized and finally combined with a microfluidic chamber...


August 2023

Diffuse-scattering-informed Geometric Channel Modeling for THz Wireless Communications Systems

Leyre Azpilicueta, Alper Schultze, Mikel Celaya-Echarri, Raed. M. Shubair, Francisco Falcone, Fidel A. Rodríguez-Corbo, Costas Constantinou, Miguel Navarro-Cía

This paper validates an in-house three-dimensional ray-launching (3D-RL) algorithm with a channel sounder measurement campaign that has been performed in a typical indoor environment at 300 GHz.


August 2023

A hybrid photonic integrated signal source with > 1.5 THz continuous tunability and < 0.25 GHz accuracy for mmW/THz applications

Tianwen Qian, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David de Felipe Mesquida, Madeleine Weigel, Jakob Reck, Klara Mihov, Martin Kresse, Peer Liebermann

We present a hybrid photonic integrated mmW/THz signal source, which comprises two tunable lasers and on-chip wavelength meters. The continuous wavelength tunability of a single laser is over 12 nm (1.5 THz), and the wavelength meter accuracy is...


August 2023

1x4 Vertical Power Splitter/Combiner: A Basic Building Block for Complex 3D Waveguide Routing Networks

Madeleine Weigel, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, D. De Felipe, Martin Kresse, Tianwen Qian, Jakob Reck, Klara Mihov, Jan H. Bach, Philipp Winklhofer

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.


Juli 2023

Optimization of Ultra-Broadband Optical Wavelength Conversion in Nonlinear Multi-Modal Silicon-On-Insulator Waveguides

Isaac Sackey, Norbert Hanik, Colja Schubert, Ronald Freund, Lars Zimmermann, Gregor Ronniger, Tasnad Kernetzky, Yizhao Jia, Ulrike Höfler

Ultra-broadband wavelength conversion is identified as one of the key issues in future high capacity, flexible optical networks. In this contribution, methods to optimize the design of a multi-modal high-nonlinear SOI waveguide to achieve...


Juli 2023

Eight-channel SiNx microring–resonator based photonic biosensor for label-free fluid analysis in the optical C-band

Jakob Reck, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David de Felipe Mesquida, Martin Kresse, Hauke Conradi, Tianwen Qian, Cafercan Yilmaz, Madeleine Weigel, Klara Mihov, Christina Hoffmann, Peter Hoffmann, Vera Froese, Ulrich Kertzscher, Kristina Mykhailiuk, Julia Michaelis, Wilfired Weigel, Sören Scholand, Hans-Jürgen Heupke

A lab-on-a-chip multichannel sensing platform for biomedical analysis based on optical silicon nitride (SiNx) mi- croring-resonators (MRR) was established. The resonators were surface functionalized and finally combined with a microfluidic...


Juli 2023

Automatic Reconstruction of Semantic 3D Models from 2D Floor Plans

Aleixo Cambeiro Barreiro, Peter Eisert, Anna Hilsmann, Mariusz Trzeciakiewicz

Digitalization of existing buildings and the creation of 3D BIM models is crucial for many tasks. Of particular importance are floor plans, which contain information about building layouts and are vital for construction, maintenance or...


Juni 2023

Accurate human body reconstruction for volumetric video

Decai Chen, Oliver Schreer, Peter Eisert, Ingo Feldmann, Markus Worchel

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...


Juni 2023

Dynamic Multi-View Scene Reconstruction Using Neural Implicit Surface

Decai Chen, Oliver Schreer, Peter Eisert, Ingo Feldmann, Haofei Lu

In this paper, we propose a template-free method to reconstruct surface geometry and appearance using neural implicit representations from multi-view videos. We leverage topology-aware deformation and the signed distance field to learn complex...


Juni 2023

Preserving Memories of Contemporary Witnesses Using Volumetric Video

Volumetric Video is a novel technology that allows the creation of dynamic 3D models of persons, which can then be integrated in any 3D environment. It is authentic and much more realistic and therefore ideal for the transfer of emotions, facial expressions and gestures, which is highly relevant in the context of preservation of contemporary witnesses and survivors of the Holocaust. Fraunhofer HHI is working on two projects in this cultural heritage. A VR documentary about the last Ger! man survivor of the Holocaust Ernst Grube has been produced together with UFA GmbH. A second project is with Dr. Eva Umlauf, the youngest Jewish survivor in the concentration camp in Auschwitz.

Oliver Schreer, Peter Eisert, Ingo Feldmann, Anna Hilsmann, Sylvain Renault, Marcus Zepp, Wieland Morgenstern, Rodrigo Mauricio Diaz Fernandez, Markus Worchel


Juni 2023

Explainable Sequence-to-Sequence GRU Neural Network for Pollution Forecasting

Sara Mirzavand Borujeni, Wojciech Samek, Leila Arras, Vignesh Srinivasan

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...


Juni 2023

Multi-View Mesh Reconstruction with Neural Deferred Shading

Markus Worchel, Oliver Schreer, Peter Eisert, Ingo Feldmann, Rodrigo Mauricio Diaz Fernandez, Weiwen Hu

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...


Juni 2023

Optimizing Explanations by Network Canonization and Hyperparameter Search

Frederick Pahde, Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Galip Ümit Yolcu

Rule-based and modified backpropagation XAI methods struggle with innovative layer building blocks and implementation-invariance issues. 

In this work we propose canonizations for popular deep neural network architectures and...


Juni 2023

Experimental Demonstration of Optical Modulation Format Identification Using SOI-based Photonic Reservoir

Guillermo von Hünefeld, Colja Schubert, Ronald Freund, Johannes Fischer, Isaac Sackey, Gregor Ronniger, Pooyan Safari, Md Mahasin Khan, Rijil Thomas, Enes Seker, Stephan Suckow, Max Lemme, David Stahl

We experimentally show modulation format identification in the optical domain using Silicon-on-Insulator-based Photonic-Integrated-Circuit (PIC) reservoir. Identification of 32 GBd single-polarization signals of 4QAM, 16QAM, 32QAM and 64QAM is...


Juni 2023

Increasing the power and spectral efficiencies of an OFDM-based VLC system through multi-objective optimization

Wesley Da Silva Costa, Volker Jungnickel, Ronald Freund, Anagnostis Paraskevopoulos, Malte Hinrichs, Higor Camporez, Maria Pontes, Marcelo Segatto, Helder Rocha, Jair Silva

In order to minimize power usage and maximize spectral efficiency in visible light communication (VLC), we use a multi-objective optimization algorithm and compare DC-biased optical OFDM (DCO-OFDM) with constant envelope OFDM (CE-OFDM)...


Juni 2023

Deep-Unfolded Adaptive Projected Subgradient Method for MIMO Detection

Jochen Fink, Slawomir Stanczak, Renato L. G. Cavalcante, Zoran Utkovski

Deep-Unfolded Adaptive Projected Subgradient Method for MIMO Detection This paper proposes a MIMO detector based on a deep unfolded superiorized adaptive projected subgradient method (APSM). By learning the design parameters of a superiorized...


Juni 2023

Comparison of Polarization Diversity Configurations of SOI Strip Waveguide-Based Dual-Polarization Wavelength Conversion for S-Band Transmission

Isaac Sackey, Colja Schubert, Carsten Schmidt-Langhorst, Robert Elschner, Tomoyuki Kato, Takeshi Hoshida, Gregor Ronniger, Hidenobu Muranaka, Shun Okada, Yu Tanaka, Tsuyoshi Yamamoto

Using wavelength conversion of our fabricated SOI strip waveguide, we compared experimentally the polarization-insensitive configuration toward S-band real-time transmission. It is found that parallel configuration is 3dB superior in in-out...


Juni 2023

Fooling State-of-the-Art Deepfake Detection with High-Quality Deepfakes

Arian Beckmann, Peter Eisert, Anna Hilsmann

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...



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