D Paranjpye
Papers
1
Total Citations
5
H-Index
1
About
Dr. D. Paranjpye is a researcher specializing in astronomical instrumentation and polarimetric imaging, with a focus on developing robust methods to enhance data quality. Their most significant contribution is the pioneering application of deep learning techniques to eliminate artefacts in polarimetric images, a critical challenge in observational astronomy. In their 2019 paper, "Eliminating artefacts in polarimetric images using deep learning," Dr. Paranjpye demonstrated how neural networks can effectively identify and remove contaminants—such as internal telescope reflections and satellite trails—that degrade polarization measurements from instruments like the Robotic Polarimeter. This work has garnered 5 citations, reflecting its niche but valuable impact in the field. By addressing a persistent source of error in polarimetric data, Dr. Paranjpye’s research enables more accurate studies of celestial magnetic fields and scattering processes. Their innovative approach bridges traditional observational techniques with modern machine learning, offering a practical solution for improving the reliability of polarimetric surveys. This work positions Dr. Paranjpye as a thoughtful contributor to the ongoing refinement of astronomical data processing methods.
Research Focus
Key Achievements
Top Papers
- 1Eliminating artefacts in polarimetric images using deep learning5 citations · 2019