Natarajan Sriraam
Orcid: 0000-0003-3790-3900Affiliations:
- Ramaiah Institute of Technology, Center for Medical Electronics and Computing, Bangalore, India
- SSN College of Engineering, Center for Biomedical Informatics and Signal Processing, Chennai, India
- Multimedia University (MMU), Center for Multimedia Computing, Cyberjaya, Malaysia (PhD 2007)
According to our database1,
Natarajan Sriraam
authored at least 33 papers
between 2003 and 2024.
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Bibliography
2024
Performance evaluation of convolution neural network models for detection of abnormal and ventricular ectopic beat cardiac episodes.
Multim. Tools Appl., July, 2024
2023
Performance evaluation of computer-aided automated master frame selection techniques for fetal echocardiography.
Medical Biol. Eng. Comput., 2023
2021
EMG-Based Essential Tremor Detection Using PSD Features With Recurrent Feedforward Back Propogation Neural Network.
Int. J. E Health Medical Commun., 2021
EEG-Based Demarcation of Yogic and Non-Yogic Sleep Patterns Using Power Spectral Analysis.
Int. J. E Health Medical Commun., 2021
2020
EEG based multi-class seizure type classification using convolutional neural network and transfer learning.
Neural Networks, 2020
Automated detection of epileptic seizures using successive decomposition index and support vector machine classifier in long-term EEG.
Neural Comput. Appl., 2020
Adaptive median feature baseline correction for improving recognition of epileptic seizures in ICU EEG.
Neurocomputing, 2020
2019
Expert Syst. Appl., 2019
Performance evaluation of DWT based sigmoid entropy in time and frequency domains for automated detection of epileptic seizures using SVM classifier.
Comput. Biol. Medicine, 2019
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
A Novel Approach for Real-Time Recognition of Epileptic Seizures Using Minimum Variance Modified Fuzzy Entropy.
IEEE Trans. Biomed. Eng., 2018
Classification of focal and non-focal EEG signals using neighborhood component analysis and machine learning algorithms.
Expert Syst. Appl., 2018
Automated epileptic seizures detection using multi-features and multilayer perceptron neural network.
Brain Informatics, 2018
2017
Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier.
J. Medical Syst., 2017
Optimal configuration of multilayer perceptron neural network classifier for recognition of intracranial epileptic seizures.
Expert Syst. Appl., 2017
Comparison of t-test ranking with PCA and SEPCOR feature selection for wake and stage 1 sleep pattern recognition in multichannel electroencephalograms.
Biomed. Signal Process. Control., 2017
Pattern recognition of spectral entropy features for detection of alcoholic and control visual ERP's in multichannel EEGs.
Brain Informatics, 2017
2016
Spectral entropy feature subset selection using SEPCOR to detect alcoholic impact on gamma sub band visual event related potentials of multichannel electroencephalograms (EEG).
Appl. Soft Comput., 2016
2012
Multi-feature Characterization of Epileptic Activity for Construction of an Automated Internet-based Annotated Classification.
J. Medical Syst., 2012
Expert Syst. Appl., 2012
Biomed. Signal Process. Control., 2012
2011
2010
Entropies based detection of epileptic seizures with artificial neural network classifiers.
Expert Syst. Appl., 2010
2009
Performance Evaluation of Computer Aided Diagnostic Tool (CAD) for Detection of Ultrasonic Based Liver Disease.
J. Medical Syst., 2009
2008
IEEE Trans. Inf. Technol. Biomed., 2008
Performance Evaluation of Neural Network and Linear Predictors for Near-Lossless Compression of EEG Signals.
IEEE Trans. Inf. Technol. Biomed., 2008
2007
IEEE Trans. Inf. Technol. Biomed., 2007
J. Medical Syst., 2007
A Pattern Matching Approach for the Estimation of Alignment Between Any Two Given DNA Sequences.
J. Medical Syst., 2007
2006
Context Based Error Modeling for Lossless Compression of EEG Signals Using Neural Networks.
J. Medical Syst., 2006
Digit. Signal Process., 2006
2003
Generalized Regression Neural Network Predictors for Lossless EEG Signal Compression.
Proceedings of the 3th International Conference on IT in Asia, 2003