| A framework for schizophrenia EEG signal classification with nature inspired optimization algorithms SK Prabhakar, H Rajaguru, SW Lee IEEE Access 8, 39875-39897, 2020 | 60 | 2020 |
| Medical text classification using hybrid deep learning models with multihead attention SK Prabhakar, DO Won Computational intelligence and neuroscience 2021 (1), 9425655, 2021 | 39 | 2021 |
| Holistic approaches to music genre classification using efficient transfer and deep learning techniques SK Prabhakar, SW Lee Expert Systems with Applications 211, 118636, 2023 | 36 | 2023 |
| WeDea: A New EEG-Based Framework for Emotion Recognition SH Kim, HJ Yang, NAT Nguyen, SK Prabhakar, SW Lee IEEE Journal of Biomedical and Health Informatics 26 (1), 264-275, 2021 | 35 | 2021 |
| Bayesian linear discriminant analysis for breast cancer classification H Rajaguru, SK Prabhakar 2017 2nd international conference on communication and electronics systems …, 2017 | 32 | 2017 |
| Schizophrenia EEG signal classification based on swarm intelligence computing SK Prabhakar, H Rajaguru, SH Kim Computational Intelligence and Neuroscience 2020 (1), 8853835, 2020 | 31 | 2020 |
| Transformation based tri-level feature selection approach using wavelets and swarm computing for prostate cancer classification SK Prabhakar, SW Lee IEEE Access 8, 127462-127476, 2020 | 30 | 2020 |
| Metaheuristic-based dimensionality reduction and classification analysis of PPG signals for interpreting cardiovascular disease SK Prabhakar, H Rajaguru, SW Lee IEEE Access 7, 165181-165206, 2019 | 29 | 2019 |
| Adaboost Classifier with dimensionality reduction techniques for Epilepsy Classification from EEG SK Prabhakar, H Rajaguru Precision Medicine Powered by pHealth and Connected Health: ICBHI 2017 …, 2018 | 29 | 2018 |
| An integrated approach for ovarian cancer classification with the application of stochastic optimization SK Prabhakar, SW Lee IEEE access 8, 127866-127882, 2020 | 28 | 2020 |
| Development of patient remote monitoring system for epilepsy classification SK Prabhakar, H Rajaguru The 16th International Conference on Biomedical Engineering: ICBME 2016, 7th …, 2017 | 28 | 2017 |
| Alcoholic EEG signal classification with Correlation Dimension based distance metrics approach and Modified Adaboost classification SK Prabhakar, H Rajaguru Heliyon 6 (12), 2020 | 27 | 2020 |
| Non linear ICA and logistic regression for classification of epilepsy from EEG signals H Rajaguru, SK Prabhakar 2017 international conference of electronics, communication and aerospace …, 2017 | 26 | 2017 |
| KNN classifier and K-means clustering for robust classification of epilepsy from EEG signals. A detailed analysis H Rajaguru, SK Prabhakar diplom. de, 2017 | 25 | 2017 |
| Logistic regression Gaussian mixture model and softmax discriminant classifier for epilepsy classification from EEG signals H Rajaguru, SK Prabhakar 2017 International Conference on Computing Methodologies and Communication …, 2017 | 24 | 2017 |
| Code converters with city block distance measures for classifying epilepsy from EEG signals SK Prabhakar, H Rajaguru Procedia Computer Science 87, 5-11, 2016 | 24 | 2016 |
| Analysis of adaboost classifier from compressed EEG features for epilepsy detection H Rajaguru, SK Prabhakar 2017 International Conference on Computing Methodologies and Communication …, 2017 | 23 | 2017 |
| Performance comparison of oral cancer classification with Gaussian mixture measures and multi layer Perceptron H Rajaguru, SK Prabhakar The 16th International Conference on Biomedical Engineering: ICBME 2016, 7th …, 2017 | 23 | 2017 |
| PCA and K-means clustering for classification of epilepsy risk levels from EEG signals—A comparitive study between them SK Prabhakar, H Rajaguru 2015 International Conference on Intelligent Informatics and Biomedical …, 2015 | 23 | 2015 |
| Performance analysis of linear layer neural networks for oral cancer classification SK Prabhakar, H Rajaguru 2017 6th ICT International Student Project Conference (ICT-ISPC), 1-4, 2017 | 22 | 2017 |
