Innovation of English teaching model based on machine learning neural network and image super resolution

摘要

At present, applying image recognition technology to promote English teaching is a kind of teaching innovation that meets the needs of the times. Therefore, based on machine learning neural network and image super-resolution, this study conducted an innovative analysis of English teaching mode. This paper combined the current situation of English teaching classroom to study and analyze English classroom, combined classroom characteristics as the basis of English teaching innovation and constructed a feature recognition model suitable for current English teaching status. Moreover, this paper formed an initial high-resolution image for low-resolution image reconstruction by sparse representation method, and then established a mixed sample spine regression model to re-estimate the high-frequency components of the initial high-resolution image to realize various behavioral characteristics of students in English teaching classroom. In addition, this article builds a verification test. The research shows that the proposed algorithm has certain effects and can provide theoretical reference for subsequent related research.