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Found 5 papers, 1 papers with code
Satellite-based feature extraction and multivariate time-series prediction of biotoxin contamination in shellfish
Our goal is to evaluate the integration of satellite data in forecasting models for predicting toxin concentrations in shellfish given forecasting horizons up to four weeks, which implies extracting a small set of useful features and assessing their impact on the predictive models.
Faster than LASER -- Towards Stream Reasoning with Deep Neural Networks
Whereas reasoning over time-annotated data with background knowledge may be challenging, due to the volume and velocity in which such data is being produced, such complex reasoning is necessary in scenarios where agents need to discover potential problems and this cannot be done with simple stream processing techniques.
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL
The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly.
Explainable Abstract Trains Dataset
The Explainable Abstract Trains Dataset is an image dataset containing simplified representations of trains.
Teaching the Machine to Explain Itself using Domain Knowledge
Moreover, we collect the domain feedback from a pool of certified experts and use it to ameliorate the model (human teaching), hence promoting seamless and better suited explanations.
