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Found 6 papers, 0 papers with code
Amélioration de la qualité d'images avec un algorithme d'optimisation inspirée par la nature
Reproducible images preprocessing is important in the field of computer vision, for efficient algorithms comparison or for new images corpus preparation.
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.
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.
