An Analysis of Public Environment-Oriented Marxist Philosophy Content Dissemination

Abstract

Marxist philosophy has always been attached to the practice. In the new age, Marxist philosophy needs to solve many problems, such as ecological destruction, environmental pollution, international conflicts, and technical innovation, and improve the integration of the Marxist philosophy system with China’s national conditions. The premise of change is practice, and the premise of practice is dissemination. Promoting the dissemination of Marxist philosophy is the cornerstone of solving the blind spot in the process of Marxist philosophy popularization. Because of the development of Internet technology, in order to ensure the validity of the uploaded videos related to Marxist philosophy on the platform, combining the research on human visual perception and the advantages of the long-term recurrent convolutional network (LRCN) model in video content recognition, an attention mechanism-based LRCN model is proposed, which simulates the attention characteristics of the human brain in the deep learning model, considers the video content globally, and makes the attention of the model fall in the effective area of the whole video. The experiment uses HMDB51, UCF101, and YouTube-8M data sets, and the results show that the LRCN model based on the attention mechanism proposed in this paper can effectively improve the accuracy of video content recognition, and it can converge quickly during training to improve the efficiency of model training.