Based on the deep learning method, the physical information of Reynolds equation is
introduced into the neural network, and a deep learning network frame (ReF-nets) is built to …

This paper proposes a light field (LF) three-dimensional (3D) particle image velocimetry
(PIV) method based on a digital refocused algorithm and 3D U-Net neural network for 3D …

Aberrations degrade the accuracy of quantitative, imaging-based measurements, like
particle image velocimetry (PIV). Adaptive optical elements can in principle correct the …

High-quality particle image characterization based on computed tomography is always
highly desired in the area of hydrodynamics and relevant applications, as the time-space …

近年来, 利用深度学习的方法从光场火焰图像中重建三维温度分布已成为辐射测温研究领域的
一个新方向. 传统的温度场重建网络仍沿用平面图像的特征提取方法, 不仅忽略了光场图像中 …

Hydrofluoroether (HFE) impurities detection is an issue related to detecting chemical
contamination within a high volume manufacturing (HVM) chiller caused by a rapid …

The three-dimensional particle image velocimetry (3D PIV) technique, as a non-intrusive
method for three-dimensional full-field velocity measurement, has garnered extensive …

Quantitative analysis of spray droplet fields plays a pivotal role in various domains,
encompassing internal combustion engine combustion diagnostics, equipment spray …

In recent years, the reconstruction of the three-dimensional (3D) temperature field from the
flame light-field image by the method of deep learning has been a new direction in radiation …

The flow field velocity is an important parameter for completely characterizing the topologies
of unsteady coherent flow structures. Synthetic aperture (SA)-based particle image …