Aktuelle Publikationen

With the growing demand for deploying Deep Learning models to the “edge”, it is paramount to develop techniques that allow to execute models within very tight and limited resource constraints. In this work we propose a software-hardware...

This paper analyzes the predictions of image captioning models with attention mechanisms beyond visualizing the attention itself. We compare the interpretability of attention heatmaps systematically against the explanations. We demonstrate that...

Precise  position  information  is  considered  as  the main  enabler  for  the  implementation  of  smart  manufacturing systems  in  Industry  4.0.  In ...

We report on the first real-time experiments with distributed MIMO and multiple users for LiFi. MIMO mode switching and angular diversity are beneficial for robust-ness. Multiuser multiplexing helps in scenarios where users have complementary...

This  paper  shows  the  feasibility  of  a  networked LiFi  system  using  a  distributed  multiple-input  multiple-output(MIMO)  link  for  optical ...

We propose a novel Deep Convolutional Neural Network formulation for network-wide QoT classification tasks and show its effectiveness for networks with significant topological differences. Our formulation achieves ~99% accuracy on large and...

We demonstrate the development of a QoT classifier over an autonomous machine-learning pipeline, the trading of the classifier over a federated marketplace, and eventually its deployment in the customer’s network as a cloud-native...

We report the automated deployment of 5G services across a latency-aware, semi-disaggregated, and virtualized metro network. We summarize the key findings in a detailed analysis of end-to-end latency, ! service setup time, and soft-failure...

We demonstrate an LED-based optical wireless link for fixed wireless access applications, at data rates of 1.5 Gbit/s over 50 m. The design is robust against vibration and the infrastructure module can be deployed, e.g., at a lamppost with no...

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...

In this paper, we introduce and validate two different hyperspectral intraoperative imaging setups and their use for the analysis of optical tissue properties. First, we present an improved multispectral filter-wheel setup integrated into a fully...

The task of detecting morphed face images has becomehighly relevant in recent years to ensure the security of automaticverification systems based on facial images, e.g.automated border control gates. Detection methods basedon Deep Neural Networks...

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...

In this book chapter we review photoconductive (PC) terahertz (THz) sources in the 1550-nm region. We contrast the two most common types of devices in the context of the two common implementations as PC switches and photomixers. We also...

Integration of a tunable DBR laser with an optical isolator in a polymer platform achieves 38 dB isolation over 17 nm tuning range and 5.6 mW output power. This is the first demonstrated integration of a DBR laser together with an optical...

The continued advancement in user interfaces comes to the era of virtual reality that requires a better understanding of how users will interact with 3D buttons in mid-air. Although virtual reality owns high levels of expressiveness and...

In this joint work with the University of Heidelberg, German Cancer Research Center, University Hospital of Erlangen we showed that multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with...

A size-reduced InP-based inverse-designed polarization rotator splitter is presented, being the first demonstration of a topology optimized passive waveguide component on InP. The manufactured device has extinction ratios >10dB for both...

Communication constraints prevent the wide-spread adoption of Federated Learning systems. In this work, we investigate Federated Distillation (FD) from the perspective of communication efficiency by analyzing the effects of active...

In collaboration with VI Systems and the University of Warsaw, HHI has demonstrated data rates of over 200 Gbit/s for the optical short haul. This was made possible by a new generation of VCSELs with over 30 GHz bandwidth in combination with...

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...

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...

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...

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...

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:...

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...

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...

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...

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...

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...