Multi Modal Classification

Multi-modal Classification is a machine learning technique that integrates data from multiple modalities to perform classification. Its goal is to enhance the accuracy and robustness of models by combining information from different sources such as visual, textual, and audio data. This technology offers significant advantages in complex scenarios by providing a more comprehensive data perspective and is widely applied in areas like sentiment analysis, medical diagnosis, and multimedia content recommendation, effectively improving the reliability and efficiency of decision-making.