Aktuelle Publikationen

September 2020

637 μW emitted terahertz power from photoconductive antennas

Robert Kohlhaas, Steffen Breuer, Lars Liebermeister, Simon Nellen, Milan Deumer, Mykhaylo P. Semtsiv, William Ted Masselink, Björn Globisch

We present photoconductive terahertz (THz) emitters based on rhodium (Rh) doped InGaAs for time-domain spectroscopy (TDS). The emitters feature a record high THz power of 637 µW. In combination with InGaAs:Rh receivers, a 6.5 THz bandwidth and a...


September 2020

Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL

Nils Strodthoff, Wojciech Samek, Tobias Schaeffter, Patrick Wagner

This paper puts forward first benchmarking results for the PTB-XL dataset, covering a variety of tasks from different ECG statement prediction tasks over age and gender prediction to signal quality assessment. We find that convolutional neural...


September 2020

Robust and Communication-Efficient Federated Learning from Non-IID Data

Felix Sattler, Klaus-Robert Müller, Wojciech Samek, Simon Wiedemann

Federated Learning comes at the cost of a significant communication overhead during training. In this work, we propose Sparse Ternary Compression (STC), a new compression framework that is specifically designed to meet the requirements of the...


August 2020

Effect of Optical Feedback on the Wavelength Tuning in DBR Lasers

Magnus Happach, David de Felipe Mesquida, Victor Nicolai Friedhoff, Gelani Irmscher, Martin Kresse, Moritz Kleinert, Crispin Zawadzki, Walter Brinker, Martin Möhrle, Norbert Keil, Werner Hofmann, Martin Schell

Optical feedback has an impact on the tunability of lasers. We created a model of a tunable distributed Bragg reflector (DBR) laser describing the effect of optical feedback from a constant reflector distance on the wavelength tuning. Theoretical...


August 2020

Accurate and Robust Neural Networks for Face Morphing Attack Detection

Clemens Peter Seibold, Peter Eisert, Anna Hilsmann, Wojciech Samek

A morphed face image is a fusion of two face images and represents biometrics of two different subjects. Embedded in an official document, it can cause immense damage, since both subjects can claim its ownership and thus share an identity. In...


August 2020

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints

Felix Sattler, Klaus-Robert Müller, Wojciech Samek

Federated Learning (FL) is currently the most widely adopted framework for collaborative training of (deep) machine learning models under privacy constraints. However, FL yields suboptimal results if the local clients’ data distributions...


Juli 2020

Monolithically Integrated InP-Based Polarization Rotator-Splitter with Simplified Fabrication Process

Hendrik Boerma, Patrick Runge, Martin Schell, Felix Ganzer, Shahram Keyvaninia

Polarization division multiplexing doubles the transmission capacity of optical communication systems. For such systems, splitters separating the TE from the TM mode are indispensable components. We design and manufacture an integrated InP-based...


Mai 2020

PTB-XL, A Large Publicly Available Electrocardiography Dataset

Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Dieter Kreiseler, Fatima I. Lunze, Wojciech Samek, Tobias Schaeffter

Electrocardiography (ECG) is increasingly supported by algorithms based on machine learning. We put forward PTB-XL, the to-date largest freely accessible clinical 12-lead ECG-waveform dataset comprising 21837 records from 18885 patients of 10...


April 2020

Artificial Intelligence in Dentistry: Chances and Challenges

Falk Schwendicke, Wojciech Samek, Joachim Krois

AI solutions have not by large entered routine dental practice, mainly due to (1) limited data availability, accessibility, structure and comprehensiveness, (2) lacking methodological rigor and standards in their development, (3) and practical...


April 2020

Going beyond Free Viewpoint: Creating Animatable Volumetric Video of Human Performances

Anna Hilsmann, Oliver Schreer, Peter Eisert, Ingo Feldmann, Philipp Fechteler, Wolfgang Paier, Wieland Morgenstern

We present an end-to-end pipeline for the creation of high-quality animatable volumetric video content of human performances. Going beyond the application of free-viewpoint volumetric video, we allow re-animation of an actor’s performance...



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