Aktuelle Publikationen

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

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

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

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

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

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

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

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

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

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...

Juni 2023

Assessing the Value of Multimodal Interfaces: A Study on Human–Machine Interaction in Weld Inspection Workstations

Paul Chojecki, Peter Eisert, Sebastian Bosse, Detlef Runde, David Przewozny, Niklas Gard, Niklas Hoerner, Dominykas Strazdas, Ayoub Al-Hamadi

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...

Juni 2023

Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations

Alexander Binder, Klaus-Robert Müller, Wojciech Samek, Grégoire Montavon, Sebastian Lapuschkin, Leander Weber

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...

Juni 2023

Revealing Hidden Context Bias in Segmentation and Object Detection through Concept-specific Explanations

Maximilian Dreyer, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin, Reduan Achtibat

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...

Juni 2023

Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models

Frederick Pahde, Wojciech Samek, Sebastian Lapuschkin, Maximilian Dreyer

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...

Juni 2023

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus

Anna Hedström, Wojciech Samek, Sebastian Lapuschkin, Marina M.-C. Höhne, Philine Bommer, Kristoffer K. Wickstrøm

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,...

Juni 2023

Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement

Leander Weber, Wojciech Samek, Alexander Binder, Sebastian Lapuschkin

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...

Juni 2023

Sydnone Methides: Intermediates between Mesoionic Compounds and Mesoionic N-Heterocyclic Olefins

Sebastian Mummel, Eike Hübner, Felix Lederle, Jan C. Namyslo, Martin Nieger, Andreas Schmidt

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...

Juni 2023

Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models

Daniel Krakowczyk, Sebastian Lapuschkin, David Robert Reich, Paul Prasse, Lena Ann Jäger, Tobias Scheffer

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...

Mai 2023

Demonstration of a 15-Mode Network Node Supported by a Field-Deployed 15-Mode Fiber

Ruben S. Luis, A. Mecozzi, Colja Schubert, F. Achten, Robert Emmerich, Nicolas Braig-Christophersen, Georg Rademacher, Hideaki Furukawa, Giammarco Di Sciullo, Andrea Marotta, Ralf Stolte, Fabio Graziosi, Cristian Antonelli, Pierre Sillard, Giuseppe Ferri, Benjamin J. Puttnam, Roland Ryf, Lauren Dallachiesa, Satoshi Shinada

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,...

Mai 2023

Semantic modeling of cell damage prediction: A machine learning approach at human-level performance in dermatology

Patrick Wagner, Jackie Ma, Maximilian Springenberg, Marius Kröger, Rose K. C. Moritz, Johannes Schleusener, Martina C. Meinke

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...

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