Multi-modal deep learning framework for damage detection in social media posts.

ABSTRACT: In crisis management, quickly identifying and helping affected individuals is key, especially when there is limited information about the survivors' conditions. Traditional emergency systems often face issues with reachability and handling large volumes of requests. Social media has become crucial in disaster response, providing important information and aiding in rescues when standard communication systems fail. Due to the large amount of data generated on social media during emergencies, there is a need for automated systems to process this information effectively and help improve emergency responses, potentially saving lives. Therefore, accurately understanding visual scenes and their meanings is important for identifying damage and obtaining useful information. Our research introduces

SUBMITTER: Zhang J 

PROVIDER: S-EPMC11419605 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature