A Physical Layer for Low Power Optical Wireless Communications
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...
Example-Based Facial Animation of Virtual Reality Avatars using Auto-Regressive Neural Networks
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...
Radiation pattern of planar optoelectronic antennas for broadband continuous-wave terahertz emission
Effects of a handlebar on standing VR locomotion
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...
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications
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...
A new concept for spatially resolved coherent detection with vertically illuminated photodetectors targeting ranging applications
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...
A Unifying Review of Deep and Shallow Anomaly Detection
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...
Pruning by Explaining: A Novel Criterion for Deep Neural Network Pruning
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...
Optoelectronic frequency-modulated continuous-wave terahertz spectroscopy with 4 THz bandwidth
Time-domain spectroscopy with terahertz frequencies typically requires complex and bulky systems. Here, the authors present an optoelectronics-based, frequency-domain terahertz sensing technique which offers competitive measurement performance in...
Inferring respiratory and circulatory parameters from electrical impedance tomography with deep recurrent models
Electrical impedance tomography (EIT) is a non-invasive imaging modality that allows a continuous assessment of changes in regional bioimpedance of different organs. One of its most common biomedical applications is monitoring regional...