858 citations · 947 across the 13 of their papers we have counts for
16 papers
Beyond Answer Confidence: A Controlled Audit of Self-Knowledge in a Black-Box Decision Model
Sharath M Shankaranarayana, Davor Runje, Jan Jannink
Decision models return probabilities intended for routing, abstention and automated action. Calibration makes those probabilities useful on average, but does not establish whether…
Deep Attention-guided Adaptive Subsampling
Sharath M Shankaranarayana, Soumava Kumar Roy, Prasad Sudhakar +1
Although deep neural networks have provided impressive gains in performance, these improvements often come at the cost of increased computational complexity and expense. In many ca…
Constrained Monotonic Neural Networks
Davor Runje, Sharath M. Shankaranarayana
Wider adoption of neural networks in many critical domains such as finance and healthcare is being hindered by the need to explain their predictions and to impose additional constr…
ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images
Huihui Fang, Fei Li, Huazhu Fu +28
Age-related macular degeneration (AMD) is the leading cause of visual impairment among elderly in the world. Early detection of AMD is of great importance, as the vision loss cause…
Attention Augmented Convolutional Transformer for Tabular Time-series
Sharath M Shankaranarayana, Davor Runje
Time-series classification is one of the most frequently performed tasks in industrial data science, and one of the most widely used data representation in the industrial setting i…
Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report
Sharath M Shankaranarayana
Age related macular degeneration (AMD) is one of the major causes for blindness in the elderly population. In this report, we propose deep learning based methods for retinal analys…
Monocular Retinal Depth Estimation and Joint Optic Disc and Cup Segmentation using Adversarial Networks
Sharath M Shankaranarayana, Keerthi Ram, Kaushik Mitra +1
One of the important parameters for the assessment of glaucoma is optic nerve head (ONH) evaluation, which usually involves depth estimation and subsequent optic disc and cup bound…
A context based deep learning approach for unbalanced medical image segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Vijaya Raghavan S +3
Automated medical image segmentation is an important step in many medical procedures. Recently, deep learning networks have been widely used for various medical image segmentation…
REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs
José Ignacio Orlando, Huazhu Fu, João Barbossa Breda +28
Glaucoma is one of the leading causes of irreversible but preventable blindness in working age populations. Color fundus photography (CFP) is the most cost-effective imaging modali…
ALIME: Autoencoder Based Approach for Local Interpretability
Sharath M. Shankaranarayana, Davor Runje
Machine learning and especially deep learning have garneredtremendous popularity in recent years due to their increased performanceover other methods. The availability of large amo…
Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +3
For the task of medical image segmentation, fully convolutional network (FCN) based architectures have been extensively used with various modifications. A rising trend in these arc…
Deep Network for Capacitive ECG Denoising
Vignesh Ravichandran, Balamurali Murugesan, Sharath M Shankaranarayana +4
Continuous monitoring of cardiac health under free living condition is crucial to provide effective care for patients undergoing post operative recovery and individuals with high c…
RespNet: A deep learning model for extraction of respiration from photoplethysmogram
Vignesh Ravichandran, Balamurali Murugesan, Vaishali Balakarthikeyan +5
Respiratory ailments afflict a wide range of people and manifests itself through conditions like asthma and sleep apnea. Continuous monitoring of chronic respiratory ailments is se…
Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation
Sharath M Shankaranarayana, Keerthi Ram, Kaushik Mitra +1
Glaucoma is a serious ocular disorder for which the screening and diagnosis are carried out by the examination of the optic nerve head (ONH). The color fundus image (CFI) is the mo…
Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +2
Image segmentation is a primary task in many medical applications. Recently, many deep networks derived from U-Net have been extensively used in various medical image segmentation…
Joint shape learning and segmentation for medical images using a minimalistic deep network
Balamurali Murugesan, Kaushik Sarveswaran, Sharath M Shankaranarayana +2
Recently, state-of-the-art results have been achieved in semantic segmentation using fully convolutional networks (FCNs). Most of these networks employ encoder-decoder style archit…