Multimodal Text And Image Classification

Multimodal Text and Image Classification is a task that combines textual and image data for classification, aiming to enhance classification accuracy and robustness through the integration of multimodal information. This task not only focuses on the features of single-modal data but also emphasizes the complementarity and interaction of cross-modal information to achieve a comprehensive understanding of complex scenarios. Its applications are extensive, including but not limited to social media analysis, product recommendation systems, medical image diagnosis, and other fields, making it of significant practical importance and commercial value.