Event-based vision sensors encode local pixel-wise brightness changes in...
Object type classification for automotive radar has greatly improved wit...
The widespread use of Deep Learning (DL) applications in science and ind...
Post-hoc calibration is a common approach for providing high-quality
con...
Uncertainty estimates help to identify ambiguous, novel, or anomalous in...
Reliably detecting anomalies in a given set of images is a task of high
...
Data-driven approaches to sequence-to-sequence modelling have been
succe...
Deep convolutional neural networks (CNNs) have shown great potential for...
Despite their advantages in terms of computational resources, latency, a...
Looking at a person's hands one often can tell what the person is going ...
Deep spiking neural networks (SNNs) hold great potential for improving t...
There is an urgent need for compact, fast, and power-efficient hardware
...
Colorectal adenocarcinoma originating in intestinal glandular structures...
Solving constraint satisfaction problems (CSPs) is a notoriously expensi...