E. Gopalakrishnan

Orcid: 0000-0003-3689-6083

According to our database1, E. Gopalakrishnan authored at least 28 papers between 2017 and 2024.

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

Timeline

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Bibliography

2024
Centralized CNN-GRU Model by Federated Learning for COVID-19 Prediction in India.
IEEE Trans. Comput. Soc. Syst., February, 2024

Deep learning-based approach for multi-stage diagnosis of Alzheimer's disease.
Multim. Tools Appl., February, 2024

Robust language independent voice data driven Parkinson's disease detection.
Eng. Appl. Artif. Intell., 2024

An analysis of data leakage and generalizability in MRI based classification of Parkinson's Disease using explainable 2D Convolutional Neural Networks.
Digit. Signal Process., 2024

A Visibility Graph Approach for Multi-Stage Classification of Parkinson's Disease Using Multimodal Data.
IEEE Access, 2024

Open Set Domain Adaptation for Classification of Dynamical States in Nonlinear Fluid Dynamical Systems.
IEEE Access, 2024

2023
Two-stage deep learning model for automate detection and classification of lung diseases.
Soft Comput., November, 2023

Explainable Deep Learning-Based Approach for Multilabel Classification of Electrocardiogram.
IEEE Trans. Engineering Management, 2023

Transfer learning approach for pediatric pneumonia diagnosis using channel attention deep CNN architectures.
Eng. Appl. Artif. Intell., 2023

Unleashing the Power of Dynamic Mode Decomposition and Deep Learning for Rainfall Prediction in North-East India.
CoRR, 2023

2022
Identification of intracranial haemorrhage (ICH) using ResNet with data augmentation using CycleGAN and ICH segmentation using SegAN.
Multim. Tools Appl., 2022

Odonata identification using Customized Convolutional Neural Networks.
Expert Syst. Appl., 2022

A Recurrence Network Approach for Characterization and Detection of Dynamical Transitions During Human Speech Production.
Circuits Syst. Signal Process., 2022

Explainable AI Framework for COVID-19 Prediction in Different Provinces of India.
CoRR, 2022

2021
Exploring fake news identification using word and sentence embeddings.
J. Intell. Fuzzy Syst., 2021

Synthetic Data Augmentation of MRI using Generative Variational Autoencoder for Parkinson's Disease Detection.
Proceedings of the Evolution in Computational Intelligence, 2021

2020
Glottal Activity Detection from the Speech Signal Using Multifractal Analysis.
Circuits Syst. Signal Process., 2020

Prediction of number of cases expected and estimation of the final size of coronavirus epidemic in India using the logistic model and genetic algorithm.
CoRR, 2020

Deep Learning Based Approach for Multiple Myeloma Detection.
Proceedings of the 11th International Conference on Computing, 2020

Analysis of Adversarial based Augmentation for Diabetic Retinopathy Disease Grading.
Proceedings of the 11th International Conference on Computing, 2020

Performance Improvement of Deep Residual Skip Convolution Neural Network for Atrial Fibrillation Classification.
Proceedings of the Evolution in Computational Intelligence, 2020

2018
Epoch Estimation from Emotional Speech Signals Using Variational Mode Decomposition.
Circuits Syst. Signal Process., 2018

Accurate Estimation of Glottal Closure Instants and Glottal Opening Instants from Electroglottographic Signal Using Variational Mode Decomposition.
Circuits Syst. Signal Process., 2018

2017
Single Sensor Techniques for Sleep Apnea Diagnosis Using Deep Learning.
Proceedings of the 2017 IEEE International Conference on Healthcare Informatics, 2017

Stock price prediction using LSTM, RNN and CNN-sliding window model.
Proceedings of the 2017 International Conference on Advances in Computing, 2017

Classification of states of bi-stable oscillator using deep learning.
Proceedings of the 2017 International Conference on Advances in Computing, 2017

Stock price prediction using dynamic mode decomposition.
Proceedings of the 2017 International Conference on Advances in Computing, 2017

Instantaneous heart rate as a robust feature for sleep apnea severity detection using deep learning.
Proceedings of the 2017 IEEE EMBS International Conference on Biomedical & Health Informatics, 2017


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