Multi Lingual Image Text Classification

Multilingual Image-Text Classification is a cross-lingual image and text joint classification technology that aims to perform comprehensive analysis of images and text in multilingual environments using deep learning models, achieving precise category division. This technology can not only handle data in a single language but also effectively deal with situations where multiple languages are mixed, significantly enhancing the understanding and management of multimedia content. Its core objective is to improve the model's generalization and cross-lingual transfer capabilities, thereby playing a crucial role in international application scenarios. This technology is widely applied in content moderation, intelligent recommendations, and multimodal search, helping to build smarter and more efficient multimedia information systems.