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We present an electrocardiogram (ECG) -based emotion recognition system using self-supervised learning. Our proposed architecture consists of two main networks, a signal transformation recognition…
A differential approach is proposed for tomographic rain field reconstruction using the estimated signal-to-noise ratio of microwave signals from low earth orbit satellites at the ground receivers,…
What is Spectrum and Signal Analysis? Hear which measurements are available, the theory of operation, modern designs, capabilities and more. An expert from Keysight Technologies defines the 3 main…
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We present a novel end-to-end network, MANet, for light field depth estimation. MANet is a parameter-effective and efficient multi-scale aggregated network, which is about 3 times smaller and 3 times…
Generic object detection algorithms have proven their excellent performance in recent years. However, object detection on underwater datasets is still less explored. In contrast to generic datasets,…
Music listening context such as location or activity has been shown to greatly influence the users' musical tastes. In this work, we study the relationship between user context and audio content in…
Acoustic analysis of sleep breathing sounds using a smartphone at home provides a much less obtrusive means of screening for sleep-disordered breathing (SDB) than assessment in a sleep clinic.…
The accuracy of video quality metrics (VQMs) is an important issue for several applications. In this work, first we observe that the accuracy of several video quality metrics (VQMs) is strongly…
Robust optimization is an important task in wireless communications, because due to fading and feedback delay there is inherent uncertainty in channel state information in a wireless environment.…
Deep-learning based speech separation models confront poor generalization problem that even the state-of-the-art models could abruptly fail when evaluating them in mismatch conditions. To address…
Computational objective metrics that use reference signals have been shown to be effective forms of speech assessment in simulated environments, since they are correlated with subjective listening…
In headset and hearing aid applications, it is of interest to retrieve the user's own voice in a noisy environment, e.g. for telephony applications. To do so, the cross power spectral density (CPSD)…
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In the context of multivariate time series, a whiteness test against an MA(1) correlation model is proposed. This test is built on the eigenvalue distribution (spectral measure) of the non-Hermitian…
Neural coding schemes are powerful tools used within neuroscience. This paper introduces three different neural coding scheme formations for event-based vision data which are designed to emulate the…
Principal Component Analysis (PCA) is a popular tool for dimension reduction and feature extraction in data analysis. Probabilistic PCA (PPCA) extends the standard PCA by using a probabilistic model…
Self supervised representation learning has recently attracted a lot of research interest for both the audio and visual modalities. However, most works typically focus on a particular modality or…
Mask-based lensless cameras offer an alternative option to conventional cameras. Compared to conventional cameras, lensless cameras can be extremely thin, flexible, and light-weight. Despite these…
This paper presents a novel 3DoF+ system that allows to navigate, i.e., change position, in scene-based spatial audio content beyond the sweet spot of a Higher Order Ambisonics recording. It is one…
The polyphonic OpenMIC-2018 dataset is based on weak and incomplete labels. The automatic classification of sound events, based on the VGGish bottleneck layer as proposed before by the AudioSet,…
The increasing demands of high resolution and quality aggravate the status of heavy burden of cluster storage side and restricted bandwidth resources. Hence, video de-duplication in storage and…
We investigate the problem of machine learning with mislabeled training data. We try to make the effects of mislabeled training better understood through analysis of the basic model and equations…
Beamspace processing is an efficient and commonly used approach in harmonic retrieval (HR). In the beamspace, measurements are obtained by linearly transforming the sensing data, thereby achieving a…
As handwriting input becomes more prevalent, the large symbol inventory required to support Chinese handwriting recognition poses unique challenges. This paper describes how the Apple deep learning…