To process multi-modal data as well as improve the robustness of deep learning models, we propose a multi-modal adversarial training method for crisis-related ...

To our best knowledge, this is the first work to classify multi- modal crisis-related social media data with adversarial training techniques. Experimental ...

This study proposes a multimodal data classification model for mining social media information. Using the model, the study employs Late Dirichlet Allocation ( ...

Jun 1, 2022 · In this paper, we propose an effective deep learning model to leverage multi-modal information sources in the form of both texts and images, and then ...

Jul 20, 2022 · This study proposes a Multi-Source Domain Adaptation framework for Disaster Management (MSDA-DM) to classify disaster images posted on social media based on ...

May 13, 2024 · We study the effectiveness of pre-trained multimodal contrastive learning models, specifically, CLIP, and ALIGN, on the task of classifying multimodal crisis ...

Oct 22, 2024 · In contrast to previous studies, this study proposes a multimodal data classification model for mining social media information. Using the model ...

This work introduces neural network based classification methods for binary and multi-class tweet classification task and shows that these models do not ...

Oct 12, 2022 · It uses common SSL techniques such as consistency regularization, sharpening and data filtering (i.e., confidence based masking and balancing), ...

Crisismmd: Multimodal twitter datasets from nat- ural disasters. In Proceedings of the 12th Interna- tional AAAI Conference on Web and Social Media. (ICWSM).