Rajitha Bakthula

Orcid: 0000-0002-2771-9950

Affiliations:
  • Motilal Nehru National Institute of Technology Allahabad, CSED, MNNIT, Prayagraj, India


According to our database1, Rajitha Bakthula authored at least 13 papers between 2015 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
$\mathrm SRC_{2}$: a novel deep learning based technique for identifying COVID-19 using images of chest x-ray.
Multim. Tools Appl., April, 2024

Hybrid framework for respiratory lung diseases detection based on classical CNN and quantum classifiers from chest X-rays.
Biomed. Signal Process. Control., February, 2024

MLDC: multi-lung disease classification using quantum classifier and artificial neural networks.
Neural Comput. Appl., 2024

2023
Secured image storage and transmission technique suitable for IoT using Tangle and a novel image encryption technique.
Multim. Tools Appl., October, 2023

Content-Based Image Retrieval: A Survey on Local and Global Features Selection, Extraction, Representation, and Evaluation Parameters.
IEEE Access, 2023

2022
Segmentation of Epiphysis Region-of-Interest (EROI) using texture analysis and clustering method for hand bone age assessment.
Multim. Tools Appl., 2022

2021
Content-based image retrieval for categorized dataset by aggregating gradient and texture features.
Neural Comput. Appl., 2021

A novel background updation algorithm using fuzzy c-means clustering for pedestrian detection.
Multim. Tools Appl., 2021

2020
Pattern-based image retrieval using GLCM.
Neural Comput. Appl., 2020

2019
Image classification using SURF and bag of LBP features constructed by clustering with fixed centers.
Multim. Tools Appl., 2019

2018
Self authenticating medical X-ray images for telemedicine applications.
Multim. Tools Appl., 2018

2017
XOR based continuous-tone multi secret sharing for store-and-forward telemedicine.
Multim. Tools Appl., 2017

2015
A new local homogeneity analysis method based on pixel intensities for image defect detection.
Proceedings of the 2nd IEEE International Conference on Recent Trends in Information Systems, 2015


  Loading...