858 citations · 946 across the 11 of their papers we have counts for
15 papers
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…