61 citations · 66 across the 9 of their papers we have counts for
10 papers
Semi-supervised Learning for Dense Object Detection in Retail Scenes
Jaydeep Chauhan, Srikrishna Varadarajan, Muktabh Mayank Srivastava
Retail scenes usually contain densely packed high number of objects in each image. Standard object detection techniques use fully supervised training methodology. This is highly co…
Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics
Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
We demonstrate the need and potential of systematically integrated vision and semantics solutions for visual sensemaking in the backdrop of autonomous driving. A general neurosymbo…
Benchmark for Generic Product Detection: A Low Data Baseline for Dense Object Detection
Srikrishna Varadarajan, Sonaal Kant, Muktabh Mayank Srivastava
Object detection in densely packed scenes is a new area where standard object detectors fail to train well. Dense object detectors like RetinaNet trained on large and dense dataset…
Out of Sight But Not Out of Mind: An Answer Set Programming Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving
Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
We demonstrate the need and potential of systematically integrated vision and semantics} solutions for visual sensemaking (in the backdrop of autonomous driving). A general method…
Multidomain Document Layout Understanding using Few Shot Object Detection
Pranaydeep Singh, Srikrishna Varadarajan, Ankit Narayan Singh +1
We try to address the problem of document layout understanding using a simple algorithm which generalizes across multiple domains while training on just few examples per domain. We…
Semantic Analysis of (Reflectional) Visual Symmetry: A Human-Centred Computational Model for Declarative Explainability
Jakob Suchan, Mehul Bhatt, Srikrishna Vardarajan +2
We present a computational model for the semantic interpretation of symmetry in naturalistic scenes. Key features include a human-centred representation, and a declarative, explain…
Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset
Srikrishna Varadarajan, Muktabh Mayank Srivastava
We propose a weakly supervised method using two algorithms to predict object bounding boxes given only an image classification dataset. First algorithm is a simple Fully Convolutio…
Detection of Tooth caries in Bitewing Radiographs using Deep Learning
Muktabh Mayank Srivastava, Pratyush Kumar, Lalit Pradhan +1
We develop a Computer Aided Diagnosis (CAD) system, which enhances the performance of dentists in detecting wide range of dental caries. The CAD System achieves this by acting as a…
Anatomical labeling of brain CT scan anomalies using multi-context nearest neighbor relation networks
Srikrishna Varadarajan, Muktabh Mayank Srivastava, Monika Grewal +1
This work is an endeavor to develop a deep learning methodology for automated anatomical labeling of a given region of interest (ROI) in brain computed tomography (CT) scans. We co…
RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans
Monika Grewal, Muktabh Mayank Srivastava, Pulkit Kumar +1
We describe a deep learning approach for automated brain hemorrhage detection from computed tomography (CT) scans. Our model emulates the procedure followed by radiologists to anal…