Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety
of application scenarios like Mixed Reality environments, touchless public kiosks …

Liquid argon time projection chambers (LArTPCs) are widely used in particle detection for
their tracking and calorimetric capabilities. The particle physics community actively builds …

Introduction Modeling multi-channel electroencephalographic (EEG) time-series is a
challenging tasks, even for the most recent deep learning approaches. Particularly, in this …

Recently, deep learning methods have achieved promising crop mapping results. Yet, their
classification performance is constrained by the scarcity of labeled samples. Therefore, the …

In this paper, we address the problem of system identification and control of a front-steered
vehicle which abides by the Ackermann geometry constraints. This problem arises naturally …

There is a growing interest in cost-effective self-supervised fine-tuning (SSFT) of self-
supervised learning (SSL)-based speech models to obtain task-specific representations …

Self-supervised learning (SSL)-based speech models are extensively used for full-stack
speech processing. However, it has been observed that improving SSL-based speech …

Biomedical sensors have been widely utilized to perform long-term health monitoring on
biosignals by being embedded into Internet-of-Things (IoT) devices. IoT-enabled health …

Liquid argon time projection chambers (LArTPCs) are widely used in particle detection for
their tracking and calorimetric capabilities. The particle physics community actively builds …

Clustering weather data is a valuable endeavor in multiple respects. The results can be
used in various ways within a larger weather prediction framework or could simply serve as …