A CNN-based shock detection method in flow visualization
type: Item
instance of: scholarly article
title: A CNN-based shock detection method in flow visualization
zbMATH Open document ID: 1411.76125
author: Yang Liu
author: Yutong Lu
author: Dong Sun
author: Liang Deng
author: Fang Wang
author: Yan Lei
author: Yueqing Wang
published in: Computers and Fluids
publication date: 2019-04-26T00:00:00Z
Mathematics Subject Classification ID: 76M27
Mathematics Subject Classification ID: 76L05
zbMATH DE Number: 7048382
zbMATH Keywords: flow visualization
zbMATH Keywords: shock detection
zbMATH Keywords: CFD flow field
describes a project that uses: darch
describes a project that uses: Faster R-CNN
describes a project that uses: SENSEI
describes a project that uses: Adam
MaRDI profile type: Publication
full work available at URL: j.compfluid.2019.03.022
OpenAlex ID: W2930722499
cites work: Drag prediction, decomposition and visualization in unstructured mesh CFD solver of TAS-code
cites work: Learning Deep Architectures for AI
cites work: Reynolds averaged turbulence modelling using deep neural networks with embedded invariance
cites work: Auto-association by multilayer perceptrons and singular value decomposition
cites work: Reducing the Dimensionality of Data with Neural Networks
cites work: Topological structure of shock induced vortex breakdown
Wikidata QID: Q128168470
DOI: 10.1016/J.COMPFLUID.2019.03.022
description: scientific article; zbMATH DE number 7048382