Search Results - "Davidson, Padraig"

IMU Airtime Detection in Snowboard Halfpipe: U-Net Deep Learning Approach Outperforms Traditional Threshold Algorithms by Gorges, Tom, Davidson, Padraig, Boeschen, Myriam, Hotho, Andreas, Merz, Christian

“…Airtime is crucial for high-rotation tricks in snowboard halfpipe performance, significantly impacting trick difficulty, the primary judging criterion. This…”
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Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study by Davidson, Padraig, Düking, Peter, Zinner, Christoph, Sperlich, Billy, Hotho, Andreas

“…The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running…”
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How stressors disrupt honey bee biological traits and overwintering mechanisms by Minaud, Étienne, Rebaudo, François, Davidson, Padraig, Hatjina, Fani, Hotho, Andreas, Mainardi, Giulia, Steffan-Dewenter, Ingolf, Vardakas, Philippos, Verrier, Elise, Requier, Fabrice

“…High winter mortality of honey bees (Apis mellifera) has been observed in temperate regions over the past 30 years. Several biotic and abiotic stressors…”
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Density-based weighting for imbalanced regression by Steininger, Michael, Kobs, Konstantin, Davidson, Padraig, Krause, Anna, Hotho, Andreas

“…In many real world settings, imbalanced data impedes model performance of learning algorithms, like neural networks, mostly for rare cases. This is especially…”
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OpenLUR: Off-the-shelf air pollution modeling with open features and machine learning by Lautenschlager, Florian, Becker, Martin, Kobs, Konstantin, Steininger, Michael, Davidson, Padraig, Krause, Anna, Hotho, Andreas

“…To assess the exposure of citizens to pollutants like NOx or particulate matter in urban areas, land use regression (LUR) models are a well established method…”
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Semi-unsupervised Learning for Time Series Classification by Davidson, Padraig, Steininger, Michael, Huhn, André, Krause, Anna, Hotho, Andreas

“…Time series are ubiquitous and therefore inherently hard to analyze and ultimately to label or cluster. With the rise of the Internet of Things (IoT) and its…”
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Anomaly Detection in Beehives: An Algorithm Comparison by Davidson, Padraig, Steininger, Michael, Lautenschlager, Florian, Krause, Anna, Hotho, Andreas

“…Sensor-equipped beehives allow monitoring the living conditions of bees. Machine learning models can use the data of such hives to learn behavioral patterns…”
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Anomaly Detection in Beehives using Deep Recurrent Autoencoders by Davidson, Padraig, Steininger, Michael, Lautenschlager, Florian, Kobs, Konstantin, Krause, Anna, Hotho, Andreas

“…Proceedings of the 9th International Conference on Sensor Networks (SENSORNETS 2020), 2020, 142-149 Precision beekeeping allows to monitor bees' living…”
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