Research on a video scene recognition model integrating multimodal information

This study aims to develop a video scene recognition model that integrates multimodal information to improve the accuracy and robustness of video scene understanding. The model combines visual, audio, and text data, and achieves effective fusion of multimodal information through efficient data preprocessing and feature extraction mechanisms. Experimental verification shows that the model exhibits excellent recognition performance in various scenarios, especially in complex scene processing, outperforming traditional single modal methods.