1 citations · 1 across the 2 of their papers we have counts for
4 papers
Detailed derivation of scale-Space Energy Density Transport Equation for Compressible Inhomogeneous Turbulent Flows
S. Arun, A. Sameen, Balaji Srinivasan +1
Scale-space energy density function, , is defined as the derivative of the two-point velocity correlation. The function E describes the turbulent kinetic…
A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis
Mahendra Khened, Avinash Kori, Haran Rajkumar +2
Histopathology tissue analysis is considered the gold standard in cancer diagnosis and prognosis. Given the large size of these images and the increase in the number of potential c…
Modelling pressure-Hessian from local velocity gradients information in an incompressible turbulent flow field using deep neural networks
Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan
The understanding of the dynamics of the velocity gradients in turbulent flows is critical to understanding various non-linear turbulent processes. The pressure-Hessian and the vis…
Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations
Vikas Dwivedi, Balaji Srinivasan
There has been rapid progress recently on the application of deep networks to the solution of partial differential equations, collectively labelled as Physics Informed Neural Netwo…