Multimodal Analysis of University Funding Education Mechanism Based on Deep Learning

Subsidizing education is one of the basic projects for building an educational power and realizing national development. In the context of evolving socio-economic landscapes and reforms in higher education, it has become a societal duty and an inescapable demand of our time to seamlessly integrate educational funding with talent cultivation in universities, particularly from the vantage point of targeted poverty alleviation. Consequently, we propose a multimodal analysis approach for establishing a scientific and rational system of university funding education, leveraging deep learning methodologies. According to the connotation of deep learning, funding, educating people, subsidizing educating people and subsidizing educating people mechanism, use big data to calculate the weight value of each index for the evaluation of college subsidizing educating people mechanism, so as to achieve multimodal analysis of college subsidizing educating people mechanism based on deep learning. The experimental results show that there are many indicators of student visits under the research method, and the satisfaction of students is higher under the multimodal mechanism of university-funded education; The operation effect of this method is more stable and the service performance is better.