Recent publications

May 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...


April 2020

Resolving Challanges in Deep Learning-Based Analyses of Histopathological Images using Explanation Methods

Miriam Hägele, Klaus-Robert Müller, Wojciech Samek, Alexander Binder, Frederick Klauschen, Sebastian Lapuschkin, Philipp Seegerer, Michael Bockmayr

This work shows the application of explainable AI (XIA) methods to resolve common challenges encountered in deep learning-based digital histopathology analyses. We investigate three types of biases and show that XAI techniques are helpful and...


March 2020

High performance BH InAs/InP QD and InGaAsP/InP QW mode-locked lasers as comb and pulse sources

Marlene Zander, Martin Schell, Martin Moehrle, Wolfgang Rehbein, Jan C. Balzer, Steffen Breuer, Dieter Franke, Kevin Kolpatzeck

Coherent comb lasers may serve as a source for multiwavelength modulators in short reach transmission, or for phase controlled OFDM channels in long reach. We explore and compare quantum dot (QD) and quantum well (QW) lasers with more than 33...


March 2020

Trends and Advancements in Deep Neural Network Communication

Felix Sattler, Thomas Wiegand, Wojciech Samek

Deep models are also being increasingly applied in distributed settings, where the data are separated by limited communication channels and privacy constraints. To address the challenges, a wide range of training and evaluation schemes have been...


February 2020

Determination of the optical properties of cholesteatoma in the spectral range of 250 to 800 nm

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Florian Uecker, Philipp Arens, Steffen Dommerich

We determine the absorption and scattering coefficients of cholesteatoma and bone. In the near-UV and visual spectrum, clear differences exist between both tissues. These differences reveal the future possibility to detect and identify,...


February 2020

Hybrid Human Modeling: Making Volumetric Video Animatable

Peter Eisert, Anna Hilsmann

Photo-realistic modeling and rendering of humans is extremely important for VR environments. While purely computer graphics modeling can achieve highly realistic human models, achieving real photo-realism with these models is computationally...


January 2020

DeepCABAC: A Universal Compression Algorithm for Deep Neural Networks

Simon Wiedemann, Heiner Kirchhoffer, Stefan Matlage, Paul Haase, Arturo Marban, Talmaj Marinc, David Neumann, Tung Nguyen, Ahmed Osman, Heiko Schwarz, Detlev Marpe, Thomas Wiegand, Wojciech Samek

This paper presents DeepCABAC, a universal compression algorithm for deep neural networks (DNNs) that through its adaptive, context-based rate modeling, allows an optimal quantization and coding of parameters. It compresses DNNs up to 5% of...


January 2020

UDSMProt: Universal Deep Sequence Models for Protein Classification

Nils Strodthoff, Wojciech Samek, Patrick Wagner, Markus Wenzel

Inferring the properties of protein from its amino acid sequence is a key problem in bioinformatics. We put forward UDSMProt, a universal deep sequence model that is pretrained on a language modeling task and finetuned on protein classification...



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