Aktuelle Publikationen

Mai 2021

Distributed Multiuser MIMO LiFi Networks for Industrial Wireless Communication

Kai Lennert Bober, Volker Jungnickel, Christoph Kottke, Dominic Schulz, Malte Hinrichs, Sreelal Maravanchery Mana, Sepideh Mohammadi Kouhini

LiFi exhibits characteristics that make it highly suitable as a wireless communication technology for industrial applications. As such, LiFi provides deterministic propagation, the potential for very high data density, use of license-free...

Mai 2021

Predicting the Binding of SARS-CoV-2 Peptides to the Major Histocompatibility Complex with Recurrent Neural Networks

Johanna Vielhaben, Nils Strodthoff, Markus Wenzel, Eva Weicken

Predicting the binding of viral peptides to the major histocompatibility complex with machine learning can potentially extend the computational immunology toolkit for vaccine development, and serve as a key component in the fight against a...

März 2021

A Physical Layer for Low Power Optical Wireless Communications

Malte Hinrichs, Volker Jungnickel, Ronald Freund, Jonas Hilt, Anagnostis Paraskevopoulos, Pablo Wilke Berenguer, Dominic Schulz, Peter Hellwig, Kai Lennert Bober

With the goal of enabling optical wireless communications for mobile devices, we assess a physical layer based on high-bandwidth on-off keying modulation. This allows for amplifier designs that avoid operation in a resistive mode, reducing their...

März 2021

Example-Based Facial Animation of Virtual Reality Avatars using Auto-Regressive Neural Networks

Wolfgang Paier, Peter Eisert, Anna Hilsmann

We present a hybrid animation approach that combines example-based and neural animation methods to create a simple, yet powerful animation regime for human faces. We introduce a light-weight auto-regressive network to transform our...

März 2021

Radiation pattern of planar optoelectronic antennas for broadband continuous-wave terahertz emission

Simon Nellen, Martin Schell, Björn Globisch, Robert Kohlhaas, Lars Liebermeister, Milan Deumer, Sebastian Lauck, Garrit William Johannes Schwanke

We measured and simulated the radiation pattern of continuous-wave terahertz emitters between 100 and 500 GHz. We could improve the radiation pattern by optimizing the connection between terahertz source and antenna:...

März 2021

Effects of a handlebar on standing VR locomotion

Paul Chojecki, Sebastian Bosse, Detlef Runde, David Przewozny, Mustafa Tevfik Lafci

VR becomes popular in neurological and rehabilitation assessments and exercises for controlled simulation of complex environments that are difficult to setup physically in a laboratory. For such tasks, VR systems have to meet higher requirements...

März 2021

Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications

Wojciech Samek, Klaus-Robert Müller, Sebastian Lapuschkin, Grégoire Montavon, Christopher J. Anders

This paper provides a timely overview of the field of explainable artificial intelligence (XAI). It explains the theoretical foundations of interpretability algorithms, outlines best practice aspects, demonstrates successful usage of XAI in...

März 2021

A new concept for spatially resolved coherent detection with vertically illuminated photodetectors targeting ranging applications

Pascal Rustige, Patrick Runge, Martin Schell, Francisco M. Soares, Jan Krause

This paper proposes a novel approach for coherent detection with double-side vertically illuminated photodetectors. Signal and local oscillator are injected collinearly from opposite sides of the photodetector chip. The concept inherently...

Februar 2021

A Unifying Review of Deep and Shallow Anomaly Detection

Lukas Ruff, Klaus-Robert Müller, Wojciech Samek, Grégoire Montavon, Jacob R. Kauffmann, Robert A. Vandermeulen, Marius Kloft, Thomas G. Dietterich

This paper gives a comprehensive overview over classic shallow and novel deep approaches to anomaly detection. We identify the common underlying principles and provide an empirical assessment of major existing methods that are enriched by the use...

Februar 2021

Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning

Seul-Ki Yeom, Klaus-Robert Müller, Wojciech Samek, Alexander Binder, Sebastian Lapuschkin, Simon Wiedemann, Philipp Seegerer

This paper proposes a novel criterion for CNN pruning inspired by neural network interpretability: The most relevant units, i.e. weights or filters, are automatically found using their relevance scores obtained from concepts of explainable AI...

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