CVAug 28, 2019
Detecting Parking Spaces in a Parcel using Satellite ImagesMurugesan Vadivel, SelvaKumar Murugan, Suriyadeepan Ramamoorthy et al.
Remote Sensing Images from satellites have been used in various domains for detecting and understanding structures on the ground surface. In this work, satellite images were used for localizing parking spaces and vehicles in parking lots for a given parcel using an RCNN based Neural Network Architectures. Parcel shapefiles and raster images from USGS image archive were used for developing images for both training and testing. Feature Pyramid based Mask RCNN yields average class accuracy of 97.56% for both parking spaces and vehicles
CLJan 2, 2018
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical TextSuriyadeepan Ramamoorthy, Selvakumar Murugan
Adverse reaction caused by drugs is a potentially dangerous problem which may lead to mortality and morbidity in patients. Adverse Drug Event (ADE) extraction is a significant problem in biomedical research. We model ADE extraction as a Question-Answering problem and take inspiration from Machine Reading Comprehension (MRC) literature, to design our model. Our objective in designing such a model, is to exploit the local linguistic context in clinical text and enable intra-sequence interaction, in order to jointly learn to classify drug and disease entities, and to extract adverse reactions caused by a given drug. Our model makes use of a self-attention mechanism to facilitate intra-sequence interaction in a text sequence. This enables us to visualize and understand how the network makes use of the local and wider context for classification.