Aktuelle Publikationen

November 2022

Towards the Interpretability of Deep Learning Models for Multi-Modal Neuroimaging: Finding Structural Changes of the Ageing Brain

Simon M. Hofmann, Klaus-Robert Müller, Wojciech Samek, Arno Villringer, Sebastian Lapuschkin, Frauke Beyer, Markus Loeffler, A. Veronica Witte, Ole Goltermann

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with...


Oktober 2022

Optical Generation and Transmission of mmWave Signals in 5G ERA: Experimental Evaluation Paradigm

Efstathios Andrianopoulos, Christos Kouloumentas, Norbert Keil, David de Felipe Mesquida, Simon Nellen, Panos Groumas, Lefteris Gounaridis, Christos Tsokos, Tianwen Qian, Herkules Avramopoulos, Adam Raptakis, Nikolaos K. Lyras

We demonstrate the generation, of a mmWave signal via the injection of an optical frequency comb (OFC) into an integrated tunable dual distributed Bragg reflector (DBR) laser as well as the fiber transmission and the processing of this signal by...


September 2022

Experimental Investigation of Information Bit Scrambling for Physical-Layer Security in Coherent Fiber-Optic Systems

Carsten Schmidt-Langhorst, Colja Schubert, Robert Elschner, Robert F. H. Fischer, Robert Emmerich, Johannes Pfeiffer, Fabian Chowanek, In-Ho Baek

We experimentally demonstrate tap-proof coherent optical 640-Gb/s transmission based on encryption-less physical layer security. Information bit scrambling combined with soft-decision error-correction coding yields favorably small security gaps,...


August 2022

Perfusion Assessment via Local Remote Photoplethysmography (rPPG)

Benjamin Kossack, Peter Eisert, Anna Hilsmann, Eric Wisotzky, Sebastian Schraven, Brigitta Globke

We present an approach to assess the perfusion of visible human tissue from RGB video files. We show that locally resolved rPPG-signals can be used for intraoperative perfusion analysis and visualization during skin and organ transplantation as...


August 2022

Explaint to not Forget: Defending Against Catastrophic Forgetting with XAI

Sami Ede, Wojciech Samek, Sebastian Lapuschkin, Leander Weber, Serop Baghdadlian, An Nguyen, Dario Zanca

The ability to continuously process and retain new information like we do naturally as humans is a feat that is highly sought after when training neural networks. Unfortunately, the traditional optimization algorithms often require large amounts...


August 2022

Customizing the Appearance of Sparks with Binary Metal Alloys

Philipp Memmel, Wolfgang Schade, Jannis Koch, Mingji Li, Eike Hübner, Felix Lederle, Martin Söftje

Alloys consisting of >65 at. % of a brightly emitting and low-boiling-point metal and a carrier metal allow achieving long-flying deeply colored sparks. Besides the color, branching of sparks is crucial for the visual appearance. Rare-earth...


August 2022

Towards the Interpretability of Deep Learning Models for Human Neuroimaging

Simon M. Hofmann, Klaus-Robert Müller, Wojciech Samek, Arno Villringer, Sebastian Lapuschkin, Frauke Beyer, Markus Loeffler, A. Veronica Witte

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with...


Juli 2022

Characterization of Dispersion-Tailored Silicon Strip Waveguide for Wideband Wavelength Conversion

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

In view of application to wideband wavelength conversion, an SOI waveguide was fabricated and characterized. Conversion of C- band WDM test signals into S- and L- bands in a single waveguide is demonstrated.


Juli 2022

DSP-Based Link Tomography for Amplifier Gain Estimation and Anomaly Detection in C+L-Band Systems

Matheus Ribeiro Sena, Ronald Freund, Robert Emmerich, Johannes K. Fischer, Mohammad Behnam Shariati, Caio Marciano Santos

In this work, we propose a spatially-resolved and wavelength-dependent DSP-based monitoring scheme to accurately estimate the spectral gain profile of C+L-band in-line Erbium-doped fiber amplifiers deployed in a 280-km single mode fiber link.


Juli 2022

Bayesian Optimization for Nonlinear System Identification and Pre-distortion in Cognitive Transmitters

Matheus Ribeiro Sena, Ronald Freund, Johannes Fischer, Robert Emmerich, Mustafa Sezer Erkilinc, Mohammad Behnam Shariati, Thomas Dippon

We present a digital signal processing (DSP) scheme that performs hyperparameter tuning (HT) via Bayesian optimization (BO) to autonomously optimize memory tap distribution of Volterra series and adapt parameters used in the synthetization of a...



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