Collaborators: Hamzah Baagil, Ali A, Derya Güngör, Ferran Galán
During times of major natural disasters, access to accurate and actionable information is paramount for emergency services and aid providers to maximize their life-saving efforts.
In this project, we focus on classifying information extracted from the CrisisMMD: Multimodal Crisis Dataset. Our primary goal is to develop binary and multiclass classification models to categorize crisis-related content, aiding in the efficient allocation of resources and assistance.
The CrisisMMD dataset serves as the foundation of our project, encompassing a diverse range of multimodal data, including text and images, collected during crisis events. These data provide valuable insights into disaster-related communication and aid decision-making.
The CrisisMMD Dataset: CrisisMMD Dataset
Restructured Kaggle Dataset: Restructured MM Crisis Dataset