Rahul Nijhawan

According to our database1, Rahul Nijhawan authored at least 15 papers between 2017 and 2024.

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

Timeline

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Links

On csauthors.net:

Bibliography

2024
VTnet+Handcrafted based approach for food cuisines classification.
Multim. Tools Appl., January, 2024

2023
Ensembled Deep Convolutional Generative Adversarial Network for Grading Imbalanced Diabetic Retinopathy Recognition.
IEEE Access, 2023

2022
An automated unsupervised deep learning-based approach for diabetic retinopathy detection.
Medical Biol. Eng. Comput., 2022

An Edge Filter Based Approach of Neural Style Transfer to the Image Stylization.
IEEE Access, 2022

Automated Deep Learning Based Approach for Albinism Detection.
Proceedings of the Recent Trends in Image Processing and Pattern Recognition, 2022

2021
A Vision-based Solution for Track Misalignment Detection.
Proceedings of the 34th SIBGRAPI Conference on Graphics, Patterns and Images, 2021

Classification and Detection of Acne on the Skin using Deep Learning Algorithms.
Proceedings of the 19th OITS International Conference on Information Technology, 2021

Identification of Diabetic Foot Ulcer in Images using Machine Learning.
Proceedings of the 19th OITS International Conference on Information Technology, 2021

2019
Hybrid Computational Intelligence Technique: Eczema Detection.
Proceedings of the TENCON 2019, 2019

Classification of Lesions in Retinal Fundus Images for Diabetic Retinopathy Using Transfer Learning.
Proceedings of the 2019 International Conference on Information Technology (ICIT), 2019

2018
Glacier Terminus Position Monitoring and Modelling Using Remote Sensing Data.
Proceedings of the Advances in Computing and Data Science, 2018

A Deep Learning Framework Approach for Urban Area Classification Using Remote Sensing Data.
Proceedings of 3rd International Conference on Computer Vision and Image Processing - CVIP 2018, Jabalpur, India, September 29, 2018

2017
An Integrated Deep Learning Framework Approach for Nail Disease Identification.
Proceedings of the 13th International Conference on Signal-Image Technology & Internet-Based Systems, 2017

A Deep Learning Hybrid CNN Framework Approach for Vegetation Cover Mapping Using Deep Features.
Proceedings of the 13th International Conference on Signal-Image Technology & Internet-Based Systems, 2017

Meta-Classifier Approach with ANN, SVM, Rotation Forest, and Random Forest for Snow Cover Mapping.
Proceedings of 2nd International Conference on Computer Vision & Image Processing, 2017


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