Preserving Memories of Contemporary Witnesses Using Volumetric Video
Oliver Schreer, Peter Eisert, Ingo Feldmann, Anna Hilsmann, Sylvain Renault, Marcus Zepp, Wieland Morgenstern, Rodrigo Mauricio Diaz Fernandez, Markus Worchel
Optimizing Explanations by Network Canonization and Hyperparameter Search
Rule-based and modified backpropagation XAI methods struggle with innovative layer building blocks and implementation-invariance issues.
In this work we propose canonizations for popular deep neural network architectures and...
Multi-View Mesh Reconstruction with Neural Deferred Shading
We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. We represent surfaces as triangle meshes and build a differentiable rendering pipeline around triangle...
Explainable Sequence-to-Sequence GRU Neural Network for Pollution Forecasting
The goal of pollution forecasting models is to allow the prediction and control of the air quality. While such deep learning models were deemed for a long time as black boxes, recent advances in eXplainable AI (XAI) allow to look through the...
Experimental Demonstration of Optical Modulation Format Identification Using SOI-based Photonic Reservoir
We experimentally show modulation format identification in the optical domain using Silicon-on-Insulator-based Photonic-Integrated-Circuit (PIC) reservoir. Identification of 32 GBd single-polarization signals of 4QAM, 16QAM, 32QAM and 64QAM is...
Increasing the power and spectral efficiencies of an OFDM-based VLC system through multi-objective optimization
In order to minimize power usage and maximize spectral efficiency in visible light communication (VLC), we use a multi-objective optimization algorithm and compare DC-biased optical OFDM (DCO-OFDM) with constant envelope OFDM (CE-OFDM)...
Deep-Unfolded Adaptive Projected Subgradient Method for MIMO Detection
Deep-Unfolded Adaptive Projected Subgradient Method for MIMO Detection This paper proposes a MIMO detector based on a deep unfolded superiorized adaptive projected subgradient method (APSM). By learning the design parameters of a superiorized...
Fooling State-of-the-Art Deepfake Detection with High-Quality Deepfakes
Due to the rising threat of deepfakes to security and privacy, it is most important to develop robust and reliable detectors. In this paper, we examine the need for high-quality samples in the training datasets of such detectors. Accordingly, we...
Assessing the Value of Multimodal Interfaces: A Study on Human–Machine Interaction in Weld Inspection Workstations
Multimodal user interfaces promise natural and intuitive human–machine interactions. However, is the extra effort for the development of a complex multisensor system justified, or can users also be satisfied with only one input modality? This...
Shortcomings of Top-Down Randomization-Based Sanity Checks for Evaluations of Deep Neural Network Explanations
While the evaluation of explanations is an important step towards trustworthy models, it needs to be done carefully, and the employed metrics need to be well-understood. Specifically model randomization testing is often overestimated and regarded...