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Sharath M Shankaranarayana
Sharath M Shankaranarayana
Other namesSharath Makki Shankaranarayana
Senior Data Scientist, Ericsson
Verified email at alumni.iitm.ac.in - Homepage
Title
Cited by
Cited by
Year
Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs
JI Orlando, H Fu, JB Breda, K Van Keer, DR Bathula, A Diaz-Pinto, ...
Medical image analysis 59, 101570, 2020
6392020
Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation
B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, J Joseph, ...
2019 41st Annual international conference of the IEEE engineering in …, 2019
1822019
ALIME: Autoencoder based approach for local interpretability
SM Shankaranarayana, D Runje
Intelligent Data Engineering and Automated Learning–IDEAL 2019: 20th …, 2019
1402019
Joint optic disc and cup segmentation using fully convolutional and adversarial networks
SM Shankaranarayana, K Ram, K Mitra, M Sivaprakasam
Fetal, Infant and Ophthalmic Medical Image Analysis: International Workshop …, 2017
1312017
Fully convolutional networks for monocular retinal depth estimation and optic disc-cup segmentation
SM Shankaranarayana, K Ram, K Mitra, M Sivaprakasam
IEEE journal of biomedical and health informatics 23 (4), 1417-1426, 2019
852019
Ecgnet: Deep network for arrhythmia classification
B Murugesan, V Ravichandran, K Ram, SP Preejith, J Joseph, ...
2018 IEEE International Symposium on Medical Measurements and Applications …, 2018
852018
RespNet: A deep learning model for extraction of respiration from photoplethysmogram
V Ravichandran, B Murugesan, V Balakarthikeyan, K Ram, SP Preejith, ...
2019 41st annual international conference of the IEEE engineering in …, 2019
662019
Adam challenge: Detecting age-related macular degeneration from fundus images
H Fang, F Li, H Fu, X Sun, X Cao, F Lin, J Son, S Kim, G Quellec, S Matta, ...
IEEE transactions on medical imaging 41 (10), 2828-2847, 2022
552022
Constrained monotonic neural networks
D Runje, SM Shankaranarayana
International Conference on Machine Learning, 29338-29353, 2023
292023
Deep network for capacitive ECG denoising
V Ravichandran, B Murugesan, SM Shankaranarayana, K Ram, ...
2019 IEEE International Symposium on Medical Measurements and Applications …, 2019
172019
Attention augmented convolutional transformer for tabular time-series
SM Shankaranarayana, D Runje
2021 International Conference on Data Mining Workshops (ICDMW), 537-541, 2021
132021
Effects of refractive index mismatch in optical CT imaging of polymer gel dosimeters
R Manjappa, S Makki S, R Kumar, R Kanhirodan
Medical physics 42 (2), 750-759, 2015
122015
A context based deep learning approach for unbalanced medical image segmentation
B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, ...
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1949-1953, 2020
102020
Hybrid analysis framework for prediction of outcomes in clinical trials
R Krishnan, J Domenech, R Jagannathan, SM Shankaranarayana
US Patent 11,101,043, 2021
72021
What Role for AI in Insurance Pricing
T Maynard, A Bordon, JB Berry, DB Baxter, W Skertic, BTMK Gotch, ...
A PREPRINT, 2019
62019
Conv-MCD: A plug-and-play multi-task module for medical image segmentation
B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, J Joseph, ...
Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019
62019
Restoration of neonatal retinal images
SM Shankaranarayana, K Ram, A Vinekar, K Mitra, M Sivaprakasam
Proceedings of the Ophthalmic Medical Image Analysis International Workshop …, 2016
62016
Automated heuristic deep learning-based modelling
R Krishnan, J Domenech, R Jagannathan, SM Shankaranarayana
US Patent App. 16/590,249, 2020
42020
Artificial intelligence enabled assessment of damage to automobiles
R Krishnan, J Domenech
US Patent App. 16/587,934, 2020
42020
Joint shape learning and segmentation for medical images using a minimalistic deep network
B Murugesan, K Sarveswaran, SM Shankaranarayana, K Ram, ...
arXiv preprint arXiv:1901.08824, 2019
42019
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