Human-computer system design of entrepreneurship education based on artificial intelligence and image feature retrieval

Abstract

The key of deep learning is how to extract abstract, deep and nonlinear target features, in which algorithm plays a crucial role. In this paper, the authors analyze the intelligent system design of entrepreneurship education classroom based on artificial intelligence and image feature retrieval. Pyramid pooling is used to transform any size feature map into fixed size feature vector, which is finally sent to the full connection layer for classification and regression. Experimental results show that the algorithm accelerates the convergence of the whole network and improves the detection speed. The education taught by entrepreneurial class is not only to help college students to seek a stable career, but also to help college students develop their own potential, cultivate entrepreneurial awareness, improve entrepreneurial quality and ability. Entrepreneurship education should not only stay in the design of subject courses, but should integrate entrepreneurship education with internet entrepreneurship practice. On this basis, we provide new countermeasures and suggestions for improving the quality and ability of college students in the process of entrepreneurial activities.