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This work analyses the temporal and spatial characteristics of bioclimatic conditions in the Lower Silesia region. The daily time values (12UTC) of meteorological variables in the period 1966–2017 from seven synoptic stations of the Institute of Meteorolog ...
The utilization of online stochastic algorithms is popular in large-scale learning settings due to their ability to compute updates on the fly, without the need to store and process data in large batches. When a constant step-size is used, these algorithms ...
Human detection and pose estimation are essential components for any artificial system responsive to the presence of humans and that react according to human-centered tasks. Robotic systems are typical examples, for which the body pose represents fine grai ...
EPFL2021
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Walking/gait speed is a key measure for daily mobility characterization. To date, various studies have attempted to design algorithms to estimate walking speed using an inertial sensor worn on the lower back, which is considered as a proper location for ac ...
Controlling phosphorus is fundamental to limit the risk of eutrophication of continental aquatic ecosystems. Integrated modelling of its concentration in the aquatic continuum requires specific tools for water bodies. However, although simple static empiri ...
2020
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In this work, we use deep unfolding to view cascaded non-linear RF systems as model-based neural networks. This view enables the direct use of a wide range of neural network tools and optimizers to efficiently identify such cascaded models. We demonstrate ...
IEEE2020
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Federated learning has emerged as an umbrella term for centralized coordination strategies in multi-agent environments. While many federated learning architectures process data in an online manner, and are hence adaptive by nature, most performance analyse ...
IEEE2020
A framework for analyzing and benchmarking climate model outputs is built upon delta-MAPS, a recently developed complex network analysis method. The framework allows for the possibility of highlighting quantifiable topological differences across data sets, ...
Accurate traffic density estimations is essential for numerous purposes like the developing successful transit policies or to forecast future traffic conditions for navigation. Current developments in the machine learning and computer systems bring the tra ...
Structural health monitoring (SHM) can be employed to reduce uncertainties in different aspects of structural analysis such as: load modeling, crack development, corrosion rates, etc. Fatigue is one of the main degradation processes of structures that caus ...
