Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal IAES International Journal of Robotics and Automation (IJRA)
Deepthi, Kakarla
Unknown Affiliation
Automotive Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Development of image super-resolution framework Shekar, Sanvi; Deepthi, Kakarla; Rahul, D.; K. S., Dhawan; Hegde, Vinay V.
IAES International Journal of Robotics and Automation (IJRA) Vol 12, No 2: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijra.v12i2.pp179-183

Abstract

There are some scenarios where the images taken are of low resolution and it is hard to judge the features from them, resulting in the need for enhancement. Super-resolution is a technique to produce a high-resolution image from a lower-resolution image. The intention here is to develop a system that enhances images of faces and satellite images by integrating these models and providing an interface to access this model. There have been various ways of achieving super-resolution using different techniques. Throughout the years, techniques involving deep learning methods, interpolation techniques, and recursive networks have been explored. We find it promising to use generative adversarial networks (GANs). The system has been deployed through Google Collaborate, Python libraries, and the TensorFlow framework. To assess the developed system, which consists of images, three metrics have been calculated. namely, peak signal-to-noise ratio, mean squared error, and structural similarity index. The model successfully demonstrated the capability of GANs by efficiently generating a high-resolution image from a low-resolution image for the given cases. The model would then be run on a standalone server for free Internet access for users to use super-resolution facial images and satellite images.
Co-Authors Hegde, Vinay V. K. S., Dhawan Rahul, D. Shekar, Sanvi