Recent publications

January 2024

Towards an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets

Rodrigo Hernangómez, Slawomir Stanczak, Martin Kasparick, Gerhard Fettweis, Daniel Schäufele, Rafail Ismayilov, Oscar Dario Ramos-Cantor, Hugues Tchouankem, Philipp Geuer, Alexandros Palaois, Cara Watermann, Mohammad Parvini, Anton Krause, Thomas Neugebauer, Jose Leon Calvo, Bo Chen

We present iV2V and iV2i+, two machine-learning datasets for industrial wireless communication. The datasets cover sidelink and cellular communication involving autonomous robots together with localization and sensing data, which can be used to...


January 2024

Integrated heterodyne laser Doppler vibrometer based on stress-optic frequency shift in silicon nitride

Adam Raptakis, Christos Kouloumentas, Norbert Keil, Moritz Kleinert, Hercules Avramopoulos, Panos Groumas, Lefteris Gounaridis, Christos Tsokos, Rene G. Heidemann, Madeleine Weigel, Efstathios Andrianopoulos, Jörn P. Epping, Thi Lan Anh Tran, Thomas Aukes, Marco Wolfer, Alexander Draebenstedt, Nikos Lyras, Dimitrios Nikolaidis, Elias Mylonas, Nikolaos Baxevanakis, Roberto Pessina, Erik Schreuder, Matthijn Dekkers, Volker Seyfried

We demonstrate a compact heterodyne Laser Doppler Vibrometer (LDV) based on the realization of optical frequency shift in the silicon nitride photonic integration ! platform (TriPleX). The system comprises a dual-polarization coherent detector...


January 2024

Hybrid integration of Polymer PICs and InP optoelectronics for WDM and SDM terabit intra-DC optical interconnects

Efstathios Andrianopoulos, Christos Kouloumentas, Patrick Runge, Norbert Keil, Martin Moehrle, Ute Troppenz, Annachiara Pagano, David de Felipe Mesquida, Michael Theurer, Martin Kresse, Hercules Avramopoulos, Anna Chiado Piat, Panos Groumas, Christos Tsokos, Paraskevas Bakopoulos, Madeleine Weigel, Maria Massaouti, Zerihun Tegegne, Giorgos Megas

This paper presents a hybrid photonic integration concept based on the use of a polymer motherboard, InP EML arrays and InP PD arrays to realize WDM and SDM Terabit optical engines operating at 100-Gb/s or even at 20! 0-Gb/s per lane. The optical...


January 2024

AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark

Sören Becker, Klaus-Robert Müller, Wojciech Samek, Sebastian Lapuschkin, Marcel Ackermann, Johanna Vielhaben

Explainable Artificial Intelligence (XAI) is targeted at understanding how models perform feature selection and derive their classification decisions. This paper explores post-hoc explanations for deep neural networks in the audio domain....


December 2023

A Performance Comparison of OFDM and Pulsed PHY Modulations in Optical Wireless Communications

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

Experimental tests of the OFDM and OOK-based PHYs in the Li-Fi standard IEEE 802.15.13-2023 show that the higher peak data rates of OFDM and the longer reach of OOK make them suitable for deployment in down- and uplink use cases, respectively.


December 2023

L4S Congestion Control Algorithm for Interactive Low Latency Applications over 5G

Jangwoo Son, Thomas Schierl, Cornelius Hellge, Yago Sanchez de la Fuente, Christian Hampe, Dominik Schnieders

In recent years, immersive applications such as Cloud XR have emerged, which require very low latency to ensure a high quality of experience. This paper presents a congestion control algorithm combined with L4S to achieve stable and low latency...


December 2023

Guard-ring free InGaAs/InP single photon avalanche diodes for C-band quantum communication

Pascal Rustige, Patrick Runge, Martin Schell, Jan Krause, Lorenz Eckoldt

We present a guard-ring free InGaAs/InP single photon avalanche diode with 20 µm diameter for the optical C-band. At 225 K, 25.6 µs dead time and 17% detection efficiency, the dark count rate is 3 kcps with 0.5% afterpulsing probability. This...


November 2023

From Empirical Measurements to Augmented Data Rates: A Machine Learning Approach for MCS Adaptation in Sidelink Communication

Asif Abdullah Rokoni, Slawomir Stanczak, Martin Kasparick, Daniel Schäufele

Due to the lack of a feedback channel in the C-V2X sidelink, finding a suitable MCS level is a difficult task. In this paper, we propose an ML approach that uses quantile prediction to predict the MCS level with the highest achievable data rate....


November 2023

Hybrid integration of Polymer PICs and InP optoelectronics for WDM and SDM terabit intra-DC optical interconnects

Efstathios Andrianopoulos, Christos Kouloumentas, Patrick Runge, Norbert Keil, Martin Moehrle, Ute Troppenz, Annachiara Pagano, David de Felipe Mesquida, Michael Theurer, Martin Kresse, Hercules Avramopoulos, Anna Chiado Piat, Panos Groumas, Christos Tsokos, Paraskevas Bakopoulos, Madeleine Weigel, Maria Massaouti, Zerihun Tegegne, Giorgos Megas

This paper presents a hybrid photonic integration concept based on the use of a polymer motherboard, InP EML arrays and InP PD arrays to realize WDM and SDM Terabit optical engines operating at 100-Gb/s or even at 20! 0-Gb/s per lane. The optical...


November 2023

Design and Characterization of Dispersion-Tailored Silicon Strip Waveguide toward Wideband Wavelength Conversion

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

One of cost-effective ways to increase the transmission capacity of current standard wavelength division multiplexing (WDM) transmission systems is to use a wavelength band other than the C-band to transmit in multi-band. We proposed the concept...


November 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...


November 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 introduce an XAI...


November 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...


November 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...


November 2023

Channel estimation with Zadoff–Chu sequences in the presence of phase errors

Sven Wittig, Wilhelm Keusgen, Michael Peter

Due to their perfect periodic autocorrelation property, Zadoff–Chu sequences are often used as stimulus signals in the measurement of radio channel responses. In this letter, the cross-correlation of a linear shift-invariant system's response to...


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...


October 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...


October 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...



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