Publications by authors named "Josiane Mothe"
The class distribution of a training dataset is an important factor which influences the performance of a deep learning-based system. Understanding the optimal class distribution is therefore crucial when building a new training set which may be costly to annotate. This is the case for histological images used in cancer diagnosis where image annotation requires domain experts.
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- The paper examines the discourse around psychiatric terms used in French tweets, extending previous research that primarily focused on English language tweets and a limited scope of mental health terminology.
- The study aims to categorize psychiatric word usage, assess the emotional tone of tweets (positive, negative, neutral), and compare findings with existing English-language studies.
- A dataset of 22,579 French tweets containing psychiatric terms was created, with 3040 tweets annotated by experts, revealing that 45% of these terms were misused in the context of the tweets.
Earth observation satellites have been capturing a variety of data about our planet for several decades, making many environmental applications possible such as change detection. Recently, deep learning methods have been proposed for urban change detection. However, there has been limited work done on the application of such methods to the annotation of unlabeled images in the case of change detection in forests.
View Article and Find Full Text PDFCOVID-19 is one of the most important topics these days, specifically on search engines and news. While fake news is easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific publications on COVID-19 and related research on PubMed, automatic computer-assisted analysis is required.
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