Hyperspectral images (HSIs), captured by different Earth observation airborne and space-
borne systems, provide rich spectral information in hundreds of bands, enabling far better …

Automatically recognizing activities of heavy construction equipment using sound data has
recently received considerable attention as a promising research area in construction …

This paper tackles post-hoc interpretability for audio processing networks. Our goal is to
interpret decisions of a trained network in terms of high-level audio objects that are also …

Snoring is a prominent characteristic of sleep-disordered breathing, and its detection is
critical for determining the severity of the upper airway obstruction and improving daily …

This article tackles two major problem settings for interpretability of audio processing
networks, post-hoc and by-design interpretation. For post-hoc interpretation, we aim to …

State-of-the-art under-determined audio source separation systems rely on supervised end-
end training of carefully tailored neural network architectures operating either in the time or …

Phase retrieval (PR) aims to recover a signal from the magnitudes of a set of inner products.
This problem arises in many audio signal processing applications which operate on a short …

Audio-visual (AV) representation learning is an important task from the perspective of
designing machines with the ability to understand complex events. To this end, we propose …

Sparse optimization problems are ubiquitous in many fields such as statistics, signal/image
processing and machine learning. This has led to the birth of many iterative algorithms to …

Sound event detection in real-world environments suffers from the interference of non-
stationary and time-varying noise. This paper presents an adaptive noise reduction method …