Application of Art Activities in Colleges and Universities Based on BP Neural Network Algorithm

Abstract

College education has also widely adopted new media technology, which has changed the previous single teaching method and enriched the teaching content. Art education plays an important role in higher education and is an indispensable part of our country’s quality education. The content, methods, and concepts of art education in colleges and universities are also changing with the advent of the new media era. New courses such as multimedia technology, network animation technology, and network advertising design have been added to the teaching curriculum system of colleges and universities for stimulating students’ interest in learning. The online network platform represented by WeChat has had a profound impact in the field of art education. Based on the technical characteristics of art works, this paper briefly classifies the characteristics of art works; the works perform the extraction of local data (picture elements); secondly, the texture feature parameters of each picture element are extracted by using the image histogram processing technology and the gray level co-occurrence matrix statistical analysis method; finally, a relatively mature machine learning model, BP, is introduced. The neural network algorithm learns the technical style characteristics of each part of the ink and wash work, so that on the whole, it can initially achieve the artistic style learning of the entire ink and wash painting.