Extracting Quantitative Streamline Information from Surface Flow Visualization Images in a Linear Cascade using Convolutional Neural Networks
Presentation / Conference Contribution
Liu, X., Ingram, G., Sims-Williams, D., & Breckon, T. P. (2024, September). Extracting Quantitative Streamline Information from Surface Flow Visualization Images in a Linear Cascade using Convolutional Neural Networks. Presented at GPPS Chania24, Chania
Surface flow visualization (SFV), specifically surface oil flow visualization, is an experimental technique that involves coating the surface with a mixture of oils and dyes before applying the flow to the subject. While investigating the surface flo... Read More about Extracting Quantitative Streamline Information from Surface Flow Visualization Images in a Linear Cascade using Convolutional Neural Networks.