Preliminary Applications of Transfer Learning and Generative Network

Abstract

Transfer learning has attracted interests because of the reduction of training costs. We applied this technique to the analyses for visualized results of computational fluid dynamics (CFD) simulations on 2-dimensional wing models. The accuracy and cost reduction were addressed. Preliminary studies of generative network have been made as well.