Recent publications

February 2022

Overview of the Neural Network Compression and Representation (NNR) Standard

Heiner Kirchhoffer, Karsten Müller, Werner Bailer, Fabien Racape, Wojciech Samek, Shan Liu, Miska M. Hannuksela, Paul Haase, Hamed Rezazadegan-Tavakoli, Francesco Cricri, Emre Aksu, Wei Jiang, Wei Wang, Swayambhoo Jain, Shahab Hamidi-Rad

Neural Network Coding and Representation (NNR) is the first international standard for efficient compression of neural networks. The NNR standard contains quantization and an arithmetic coding scheme as core encoding and decoding technologies, as...


January 2022

Automated Damage Inspection of Power Transmission Towers from UAV Images

Aleixo Cambeiro Barreiro, Peter Eisert, Anna Hilsmann, Clemens Peter Seibold

This paper adresses the problem of structural damage detection in transmission towers, addressing these two common challenges: (i) the lack of freely available training data and the difficulty to collect it; (ii) fuzzy boundaries of what...


January 2022

Continuous wave terahertz receivers with 4.5 THz bandwidth and 112 dB dynamic range

Milan Deumer, Martin Schell, Simon Nellen, Björn Globisch, Robert Kohlhaas, Lars Liebermeister, Steffen Breuer, Sebastian Lauck

We present photomixers made of InGaAs:Fe as broadband receivers in optoelectronic cw THz systems. The improved resistivity and carrier lifetime of InGaAs:Fe enable us to measure a bandwidth of 4.5 THz with a peak dynamic range of 112 dB. When...


January 2022

ML-assisted QoT estimation: a dataset collection and data visualization for dataset quality evaluation

Geronimo Bergk, Johannes Fischer, Mohammad Behnam Shariati, Pooyan Safari

We present a publicly available dataset collection to open the problem of data-driven QoT estimation to the ML community. The dataset collection allows comparing various solutions presented by different research groups. Furthermore, we propose...


January 2022

Explaining Machine Learning Models for Clinical Gait Analysis

Djordje Slijepcevic, Wojciech Samek, Sebastian Lapuschkin, Fabian Horst, Wolfgang I. Schöllhorn, Matthias Zeppelzauer, Anna-Maria Raberger, Christian Breiteneder, Brian Horsak, Andreas Kranzl

This article investigates the usefulness of Explainable Artificial Intelligence (XAI) methods to increase transparency in automated clinical gait classification based on time series. For this purpose, predictions of state-of-the-art...


January 2022

Finding and Removing Clever Hans: Using Explanation Methods to Debug and Improve Deep Models

Christopher J. Anders, Klaus-Robert Müller, Wojciech Samek, Sebastian Lapuschkin, David Neumann, Leander Weber

Contemporary learning models for computer vision are typically trained on very large (benchmark) datasets with millions of samples. These may, however, contain biases, artifacts, or errors that have gone unnoticed and are exploitable by the...


December 2021

Terahertz Multilayer Thickness Measurements: Comparison of Optoelectronic Time and Frequency Domain Systems

Lars Liebermeister, Martin Schell, Simon Nellen, Björn Globisch, Robert Kohlhaas, Steffen Breuer, Milan Deumer, Sebastian Lauck

We compare a state-of-the-art terahertz (THz) time domain spectroscopy (TDS) system and a novel optoelectronic frequency domain spectroscopy (FDS) system with respect to their performance in layer thickness measurements on dielectric samples....


December 2021

Inverse kinematics for full-body self representation in VR-based cognitive rehabilitation

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

Being self-represented through an avatar increases embodiment and the feeling of presence in virtual reality. Nevertheless, currently users in VR are typically represented only by their hands, as not enough tracking data is available for full...


December 2021

Accurate human body reconstruction for volumetric video

Decai Chen, Oliver Schreer, Peter Eisert, Ingo Feldmann, Markus Worchel

In this work, we enhance a professional end-to-end volumetric video production pipeline to achieve high-fidelity human body reconstruction using only passive cameras.We introduce and optimize deep learning based multi-view stereo networks for...


November 2021

Fiber-based Frequency Modulated LiDAR With MEMS Scanning Capability for Long-range Sensing in Automotive Applications

Sarah Cwalina, Volker Jungnickel, Patrick Runge, Ronald Freund, Christoph Kottke, Pascal Rustige, Thomas Knieling, Shansan Gu-Stoppel, Jörg Albers, Norman Laske, Frank Senger, Lianzhi Wen, Fabio Giovanneschi, Erdem Altuntac, Avinash Nittur Ramesh, Maria Antonia Gonzalez Huici, Andries Küter, Sangeeta Reddy

Safe operation of driver assistance systems remains a challenge, especially at higher speeds. It requires sensor technology that is capable of detecting surrounding conditions even at large distances. LiDAR technology is a cornerstone of this...



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