Research on environmental landscape design based on virtual reality technology and deep learning

Abstract Virtual Reality (VR) provides immersive visualization and intuitive interaction. The VR is used to enable any biomedical profession to develop a deep learning (DL) model for image classification. The Deep Neural Network (DNN) models can be used as a powerful tool for data analysis, but they are also challenging to understand and develop. To make deep learning more convenient and fast operation, it have established a landscape of DNN development environment based on virtual reality. In this environment, users can move concrete objects only to build neural networks with their own hands. It automatically transforms these configurations into a trainable model and reports on the real-time test dataset. In addition to realizing the insights users are developing into DNN models, it has also visually enriched the virtual environmental landscape objects with the parts of the model. In this way bridge the gap between professionals in different disciplines, providing a new perspective on the model analysis and data interaction. This system further demonstrates that learning and visualization technologies developed in Shenzhen can benefit from integrating virtual reality.