In this paper, we propose SRL4NLP, a new approach for data augmentation by drawing an
analogy between image and text processing: Super-resolution learning. This method is …

Over the past few decades, disaster assessment and management have made extensive
use of data from social media platforms. Tens of millions of tweets, either text, images, or …

The rapid growth of Internet-based communication technologies in the form of Social Media
(SM) and associated mobile applications has enabled people to share information related to …

Twitter is a useful tool for effectively tracking and managing crisis-related incidents.
However, due to many irrelevant features in textual data, the problem of high dimensionality …

Disastrous situations pose a formidable challenge, testing our resilience against nature's
fury and the race against time to prevent the loss of human life. It is noted that in such …

This paper aims at measuring transfer learning performances across different types of crises
related to sudden or unexpected events (like earthquakes, terror attacks, explosions …

Le traitement de données provenant de réseaux sociaux en temps réel est devenu une outil
attractifdans les situations d'urgence, mais la surcharge d'informations reste un défi à …

Traditionally, disaster management has placed a great emphasis on institutional warning
systems, and people have been treated as victims rather than active participants. However …