Beyond Explaining: Opportunities and Challenges of XAI-Based Model Improvement
Explainable Artificial Intelligence (XAI) is an emerging research field bringing transparency to highly complex and opaque machine learning (ML) models. This paper offers a comprehensive overview over techniques that apply XAI practically to...
Sydnone Methides: Intermediates between Mesoionic Compounds and Mesoionic N-Heterocyclic Olefins
Sydnone methides represent an almost unknown class of mesoionic compounds which possess exocyclic carbon substituents instead of oxygen (sydnones) or nitrogen (sydnone imines) in the 5-position of a 1,2,3-oxadiazolium ring. Unsubstituted...
Bridging the Gap: Gaze Events as Interpretable Concepts to Explain Deep Neural Sequence Models
Recent work in XAI for eye tracking data has evaluated the suitability of feature attribution methods to explain the output of deep neural sequence models for the task of oculomotric biometric identification. In this work, we employ established...
Semantic modeling of cell damage prediction: A machine learning approach at human-level performance in dermatology
In this work we investigate cell damage in whole slice images of the epidermis. A common way for pathologists to annotate a score, characterising the degree of damage for these samples, is the ratio between healthy and unhealthy nuclei. The...
Experimental and Numerical Evaluation of CAZAC-type Training Sequences for MxM SDM-MIMO Channel Estimation
In this work, we experimentally and numerically compare cyclic shifted constant-amplitude zero-autocorrelation (CAZAC) training sequences (TS) with different number of repetitions, sequence lengths and scalings for channel estimation in an...
Demonstration of a 15-Mode Network Node Supported by a Field-Deployed 15-Mode Fiber
Researchers from NICT, University of L’Aquila, Finisar, Prysmian and Nokia Bell Lab demonstrate a 2-line side 15-mode spatial division multiplexing network node based on fifteen 2×2 wavelength cross-connects to direct up to six 5 Tb/s, 15-mode,...
Data Models for Dataset Drift Controls in Machine Learning With Optical Images
In this study, we pair traditional machine learning with physical optics to obtain explicit and differentiable data models. We demonstrate how such data models can be constructed for image data and used to control downstream machine learning...
Telepresence for surgical assistance and training using eXtended reality during and after pandemic periods
Existing challenges in surgical education (See one, do one, teach one) as well as the COVID-19 pandemic make it necessary to develop new ways for surgical training. This work describes the implementation of a scalable remote solution called...
Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies
The Berlin V2X dataset offers high-resolution GPS-located wireless measurements across diverse urban environments in the city of Berlin for both cellular and sidelink radio access technologies, including information on the physical layer,...
1x4 Vertical Power Splitter/Combiner: A Basic Building Block for Complex 3D Waveguide Routing Networks
A novel polymer-based 1x4 vertical multimode interference (MMI) coupler for 3D photonics is presented. It connects four vertically stacked waveguide layers with a spacing of 21.6 µm. The functionality is demonstrated on a fabricated device.