Aktuelle Publikationen

März 2022

Hybrid Polymer THz Receiver PIC with Waveguide Integrated Photoconductive Antenna: Concept and 1st Characterization Results

Tianwen Qian, Norbert Keil, Martin Schell, Moritz Kleinert, Crispin Zawadzki, David DeFelipe, Moritz Baier, Simon Nellen, Björn Globisch, Hauke Conradi, Milan Deumer, Y Durvasa Gupta, Madeleine Weigel, Jakob Reck, Klara Mihov, Ben Schuler, Martin Kresse

An all-photonic THz-receiver PIC comprising an on-chip frequency stabilization scheme and a novel InP-based photoconductive antenna is presented in this paper. Characterization of the key photonic building blocks shows the functionality of the...


Februar 2022

Characterization, Monitoring, and Mitigation of Standard C-Band Transceivers I/Q Imbalance in Multiband Systems

Gabriele Di Rosa, Colja Schubert, Ronald Freund, Johannes Fischer, Andre Richter, Robert Emmerich, Matheus Ribeiro Sena

To keep up with the rapid growth in global traffic, next-generation optical communication networks aim to vastly increase capacity by exploiting a larger optical transmission window covering the S-C-L-band. To reuse current commercially available...


Februar 2022

Imposing Temporal Consistency on Deep Monocular Body Shape and Pose Estimation

Alexandra Zimmer, Peter Eisert, Anna Hilsmann, Wieland Morgenstern

We present a solution for Accurate and temporally consistent modeling of human performances from video sequences. In detail, we derive parameters of a sequence of body models, representing shape and motion of a person, including jaw poses, facial...


Februar 2022

From Explanations to Segmentation: Using Explainable AI for Image Segmentation

Johannes Wolf Künzel, Peter Eisert, Anna Hilsmann, Clemens Peter Seibold

The new era of image segmentation leveraging the power of Deep Neural Nets (DNNs) comes with a price tag: to train a neural network for pixel-wise segmentation, a large amount of training samples has to be manually labeled on pixel-precision. In...


Februar 2022

Combining Local and Global Pose Estimation for Precise Tracking of Similar Objects

Niklas Gard, Peter Eisert, Anna Hilsmann

We present a multi-object 6D detection and tracking pipeline for potentially similar and non-textured objects. The combination of a convolutional neural network for object classification and rough pose estimation with a local pose refinement and...


Februar 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...


Januar 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...


Januar 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...


Januar 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...


Januar 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...


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