KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch
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Progress in computing capabilities has enhanced science in many ways. In recent years, various branches of machine learning have been the key facilitators in forging new paths, ranging from categorizing big data to instrumental control, from materials desi ...
Deep learning algorithms are responsible for a technological revolution in a variety oftasks including image recognition or Go playing. Yet, why they work is not understood.Ultimately, they manage to classify data lying in high dimension – a feat generical ...
2021
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered a ...
Wiley2021
The current information landscape is characterised by a vast amount of relatively semantically homogeneous, when observed in isolation, data silos that are, however, drastically semantically fragmented when considered as a whole. Within each data silo, inf ...
Wearable solutions based on Deep Learning (DL) for real-time ECG monitoring are a promising alternative to detect life-threatening arrhythmias. However, DL models suffer of a large memory footprint, which hampers their adoption in portable technologies. Th ...
IEEE2021
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Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capturing ...
2020
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Touch is commonly used to mediate human-machine interactions, notably in the setting of Digital Musical Instruments (DMIs), where touch screens are prevalent. The lack of rich haptic feedback has an impact on the richness and quality of the interaction. Pi ...
IEEE2021
Structural Health Monitoring (SHM) has greatly benefited from computer vision. Recently, deep learning approaches are widely used to accurately estimate the state of deterioration of infrastructure. In this work, we focus on the problem of bridge surface s ...
2020
Artificial intelligence (AI) and machine learning (ML) have become de facto tools in many real-life applications to offer a wide range of benefits for individuals and our society. A classic ML model is typically trained with a large-scale static dataset in ...
We study the problem of landuse characterization at the urban-object level using deep learning algorithms. Traditionally, this task is performed by surveys or manual photo interpretation, which are expensive and difficult to update regularly. We seek to ch ...
