Sharath M. Shankaranarayana

Orcid: 0000-0003-3482-4887

According to our database1, Sharath M. Shankaranarayana authored at least 22 papers between 2017 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Bibliography

2024
A Hybrid Sampling Methodology Based Cost Effective Active Learning for Tabular Data.
Proceedings of the 16th International Conference on COMmunication Systems & NETworkS, 2024

2023
Model Uncertainty based Active Learning on Tabular Data using Boosted Trees.
CoRR, 2023

Constrained Monotonic Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

2022
ADAM Challenge: Detecting Age-Related Macular Degeneration From Fundus Images.
IEEE Trans. Medical Imaging, 2022

ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images.
CoRR, 2022

2021
Attention Augmented Convolutional Transformer for Tabular Time-series.
Proceedings of the 2021 International Conference on Data Mining, 2021

2020
REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs.
Medical Image Anal., 2020

Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report.
CoRR, 2020

Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks.
CoRR, 2020

A Context Based Deep Learning Approach for Unbalanced Medical Image Segmentation.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019
Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation.
IEEE J. Biomed. Health Informatics, 2019

REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs.
CoRR, 2019

RespNet: A deep learning model for extraction of respiration from photoplethysmogram.
CoRR, 2019

Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation.
CoRR, 2019

Joint shape learning and segmentation for medical images using a minimalistic deep network.
CoRR, 2019

Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 10th International Workshop, 2019

Deep Network for Capacitive ECG Denoising.
Proceedings of the IEEE International Symposium on Medical Measurements and Applications, 2019

ALIME: Autoencoder Based Approach for Local Interpretability.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

2018
A Bottom-Up Saliency Estimation Approach for Neonatal Retinal Images.
Proceedings of the Computational Pathology and Ophthalmic Medical Image Analysis, 2018

ECGNet: Deep Network for Arrhythmia Classification.
Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications, 2018

2017
Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks.
Proceedings of the Fetal, Infant and Ophthalmic Medical Image Analysis, 2017


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