Functional data analysis (FDA) is a statistical framework that allows for the analysis of
curves, images, or functions on higher dimensional domains. The goals of FDA, such as …

The performance of a machine learning model degrades when it is applied to data from a
similar but different domain than the data it has initially been trained on. To mitigate this …

Semi-structured networks (SSNs) merge the structures familiar from additive models with
deep neural networks, allowing the modeling of interpretable partial feature effects while …

Offline signature forgery detection has attracted many researchers in recent years. In real
situations, signatures should be detected from the signed documents and verified by the …

Handwriting with digital pens is a common way to facilitate human–computer interaction
through the use of online handwriting (OH) trajectory reconstruction. In this work, we focus …

Handwriting is one of the most frequently occurring patterns in everyday life and with it
comes challenging applications such as handwriting recognition, writer identification and …

The localization of objects is essential in many applications, such as robotics, virtual and
augmented reality, and warehouse logistics. Recent advancements in deep learning have …

Cross-modal representation learning learns a shared embedding between two or more
modalities to improve performance in a given task compared to using only one of the …

For many applications, analyzing the uncertainty of a machine learning model is
indispensable. While research of uncertainty quantification (UQ) techniques is very …

Although automated test generation is common in many programming domains, games still
challenge test generators due to their heavy randomisation and hard-to-reach program …