MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641049986 A) filed by Srinivasa Ramanujan Institute Of Technology; Dr. C. Lakshmi Pathi; Dr. K. Evangili Supriya; Mr. M. Pulla Reddy; Mrs. K. Bharathi; Ms. J. Ankitha; Dr. P. Divya Vani; Mrs. Surakanti Laxmi; and Dr. Y. Venkata Rangaiah, Anantapuramu, Andhra Pradesh, on April 20, for 'super-resolved satellite images via physics constrained neural network.'
Inventor(s) include Srinivasa Ramanujan Institute Technology; Dr. C. Lakshmi Pathi; Dr. K. Evangili Supriya; Mr. M. Pulla Reddy; Mrs. K. Bharathi; Ms. J. Ankitha; Dr. P. Divya Vani; Mrs. Surakanti Laxmi; and Dr. Y. Venkata Rangaiah.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "Physics-informed neural networks (NN) are an emerging technique to improve spatial resolution and enforce physical consistency of data from physics models or satellite observations. A super-resolution (SR) technique is explored to reconstruct high-resolution images (4x) from lower resolution images in an advection-diffusion model of atmospheric pollution plumes. SR performance is generally increased when the advection-diffusion equation constrains the NN in addition to conventional pixel-based constraints. The ability of SR techniques to also reconstruct missing data is investigated by randomly removing image pixels from the simulations and allowing the system to learn the content of missing data. Improvements in S/N of 11% are demonstrated when physics equations are included in SR with 40% pixel loss. Physics-informed NNs accurately reconstruct corrupted images and generate better results compared to the standard SR approaches."
Disclaimer: Curated by HT Syndication.
