| Parkinson’s disease classification from magnetic resonance images (MRI) using deep transfer learned convolutional neural networks IK Veetil, EA Gopalakrishnan, V Sowmya, KP Soman 2021 IEEE 18th India Council International Conference (INDICON), 1-6, 2021 | 18 | 2021 |
| Ensemble of deep transfer learning models for parkinson's disease classification K Rajanbabu, IK Veetil, V Sowmya, EA Gopalakrishnan, KP Soman Soft Computing and Signal Processing: Proceedings of 3rd ICSCSP 2020, Volume …, 2022 | 17 | 2022 |
| Synthetic data augmentation of MRI using generative variational autoencoder for Parkinson’s disease detection Y Madan, IK Veetil, S V, G EA, S KP Evolution In Computational Intelligence: Proceedings Of The 9th …, 2022 | 16 | 2022 |
| Deep learning-based approach for Parkinson’s disease detection using region of interest Y Madan, IK Veetil, V Sowmya, EA Gopalakrishnan, KP Soman Intelligent Sustainable Systems: Proceedings of ICISS 2021, 1-13, 2021 | 11 | 2021 |
| Robust language independent voice data driven Parkinson’s disease detection IK Veetil, V Sowmya, JR Orozco-Arroyave, EA Gopalakrishnan Engineering Applications of Artificial Intelligence 129, 107494, 2024 | 5 | 2024 |
| V, S., EA, G., & KP, S.,“Synthetic Data Augmentation of MRI using Generative Variational Autoencoder for Parkinson’s Disease Detection” Y Madan, IK Veetil Evolution in Computational Intelligence: Proceedings of the 9th …, 0 | 5 | |
| An analysis of data leakage and generalizability in MRI based classification of Parkinson's Disease using explainable 2D Convolutional Neural Networks IK Veetil, DE Chowdary, PN Chowdary, V Sowmya, EA Gopalakrishnan Digital Signal Processing 147, 104407, 2024 | | 2024 |
Gopalakrishnan E AAssociate Professor, Amrita School of Artificial Intelligence Bangalore在 blr.amrita.edu 的电子邮件经过验证
