Joint Optic Disc and Cup Segmentation Using Fully Convolutional and Adversarial Networks. - Sharath M. Shankaranarayana; Keerthi Ram; Kaushik Mitra; Mohanasankar Sivaprakasam (FIFI/OMIA@MICCAI, 2017)

ECGNet: Deep Network for Arrhythmia Classification. - Balamurali Murugesan; Vignesh Ravichandran; Keerthi Ram; S. P. Preejith; Jayaraj Joseph; Sharath M. Shankaranarayana; Mohanasankar Sivaprakasam (MeMeA, 2018)

A Bottom-Up Saliency Estimation Approach for Neonatal Retinal Images. - Sharath M. Shankaranarayana; Keerthi Ram; Anand Vinekar; Kaushik Mitra; Mohanasankar Sivaprakasam (COMPAY/OMIA@MICCAI, 2018)

Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation. - Balamurali Murugesan; Kaushik Sarveswaran; Sharath M. Shankaranarayana; Keerthi Ram; Jayaraj Joseph; Mohanasankar Sivaprakasam (EMBC, 2019)

ALIME: Autoencoder Based Approach for Local Interpretability. - Sharath M. Shankaranarayana; Davor Runje (IDEAL (1), 2019)

Deep Network for Capacitive ECG Denoising. - Vignesh Ravichandran; Balamurali Murugesan; Sharath M. Shankaranarayana; Keerthi Ram; Preejith S. P; Jayaraj Joseph; Mohanasankar Sivaprakasam (MeMeA, 2019)

Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation. - Balamurali Murugesan; Kaushik Sarveswaran; Sharath M. Shankaranarayana; Keerthi Ram; Jayaraj Joseph; Mohanasankar Sivaprakasam (MLMI@MICCAI, 2019)

Joint shape learning and segmentation for medical images using a minimalistic deep network. - Balamurali Murugesan; Kaushik Sarveswaran; Sharath M. Shankaranarayana; Keerthi Ram; Mohanasankar Sivaprakasam (CoRR, 2019)

Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation. - Balamurali Murugesan; Kaushik Sarveswaran; Sharath M. Shankaranarayana; Keerthi Ram; Mohanasankar Sivaprakasam (CoRR, 2019)

RespNet: A deep learning model for extraction of respiration from photoplethysmogram. - Vignesh Ravichandran; Balamurali Murugesan; Vaishali Balakarthikeyan; Sharath M. Shankaranarayana; Keerthi Ram; S. P. Preejith; Jayaraj Joseph; Mohanasankar Sivaprakasam (CoRR, 2019)

REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs. - José Ignacio Orlando; Huazhu Fu; João Barbosa Breda; Karel van Keer; Deepti R. Bathula; Andrés Diaz-Pinto; Ruogu Fang; Pheng-Ann Heng; Jeyoung Kim; Joonho Lee; Joonseok Lee; Xiaoxiao Li; et al. (CoRR, 2019)

Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation. - Sharath M. Shankaranarayana; Keerthi Ram; Kaushik Mitra; Mohanasankar Sivaprakasam (IEEE J. Biomed. Health Informatics, 2019)

A Context Based Deep Learning Approach for Unbalanced Medical Image Segmentation. - Balamurali Murugesan; Kaushik Sarveswaran; Vijaya Raghavan S; Sharath M. Shankaranarayana; Keerthi Ram; Mohanasankar Sivaprakasam (ISBI, 2020)

Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks. - Sharath M. Shankaranarayana; Keerthi Ram; Kaushik Mitra; Mohanasankar Sivaprakasam (CoRR, 2020)

Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report. - Sharath M. Shankaranarayana (CoRR, 2020)

REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs. - José Ignacio Orlando; Huazhu Fu; João Barbosa Breda; Karel van Keer; Deepti R. Bathula; Andrés Diaz-Pinto; Ruogu Fang; Pheng-Ann Heng; Jeyoung Kim; Joonho Lee; Joonseok Lee; Xiaoxiao Li; et al. (Medical Image Anal., 2020)

Attention Augmented Convolutional Transformer for Tabular Time-series. - Sharath M. Shankaranarayana; Davor Runje (ICDM (Workshops), 2021)

ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images. - Huihui Fang; Fei Li 021; Huazhu Fu; Xu Sun 006; Xingxing Cao; Fengbin Lin; Jaemin Son; Sunho Kim; Gwenolé Quellec; Sarah Matta; Sharath M. Shankaranarayana; Yi-Ting Chen; et al. (CoRR, 2022)

ADAM Challenge: Detecting Age-Related Macular Degeneration From Fundus Images. - Huihui Fang; Fei Li 021; Huazhu Fu; Xu Sun 006; Xingxing Cao; Fengbin Lin; Jaemin Son; Sunho Kim; Gwenolé Quellec; Sarah Matta; Sharath M. Shankaranarayana; Yi-Ting Chen; et al. (IEEE Trans. Medical Imaging, 2022)

Model Uncertainty based Active Learning on Tabular Data using Boosted Trees. - Sharath M. Shankaranarayana (AIMLSystems, 2023)

Constrained Monotonic Neural Networks. - Davor Runje; Sharath M. Shankaranarayana (ICML, 2023)

A Hybrid Sampling Methodology Based Cost Effective Active Learning for Tabular Data. - Sharath M. Shankaranarayana; Anubhab Samal; Chikka Veera Raghavendra; Vijay Sankar; Arindam Dey 004; Sangam Kumar Singh (COMSNETS, 2024)