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Found 9 papers, 0 papers with code
Astronomical Images Quality Assessment with Automated Machine Learning
Electronically Assisted Astronomy consists in capturing deep sky images with a digital camera coupled to a telescope to display views of celestial objects that would have been invisible through direct observation.
MILAN Sky Survey, a dataset of raw deep sky images captured during one year with a Stellina automated telescope
Modern automated telescopes allow to capture astronomical images in a reproducible way.
Forecasting Intraday Power Output by a Set of PV Systems using Recurrent Neural Networks and Physical Covariates
We build upon a physical, deterministic PV performance model, the output of which is used as covariates in the context of the neural model.
Cold Start Active Learning Strategies in the Context of Imbalanced Classification
We present novel active learning strategies dedicated to providing a solution to the cold start stage, i. e. initializing the classification of a large set of data with no attached labels.
Computing flood probabilities using Twitter: application to the Houston urban area during Harvey
In this paper, we investigate the conversion of a Twitter corpus into geo-referenced raster cells holding the probability of the associated geographical areas of being flooded.
Extracting localized information from a Twitter corpus for flood prevention
In this paper, we discuss the collection of a corpus associated to tropical storm Harvey, as well as its analysis from both spatial and topical perspectives.
Data-driven forecasting of solar irradiance
This paper describes a flexible approach to short term prediction of meteorological variables.
Benchmarking multimedia technologies with the CAMOMILE platform: the case of Multimodal Person Discovery at MediaEval 2015
In this paper, we claim that the CAMOMILE collaborative annotation platform (developed in the framework of the eponymous CHIST-ERA project) eases the organization of multimedia technology benchmarks, automating most of the campaign technical workflow and enabling collaborative (hence faster and cheaper) annotation of the evaluation data.
The CAMOMILE Collaborative Annotation Platform for Multi-modal, Multi-lingual and Multi-media Documents
In this paper, we describe the organization and the implementation of the CAMOMILE collaborative annotation framework for multimodal, multimedia, multilingual (3M) data.
