75 citations · 144 across the 19 of their papers we have counts for
7 papers · 1 filter
Train Once, Test Anywhere: Zero-Shot Learning for Text Classification
Pushpankar Kumar Pushp, Muktabh Mayank Srivastava
Zero-shot Learners are models capable of predicting unseen classes. In this work, we propose a Zero-shot Learning approach for text categorization. Our method involves training mod…
Boosted Cascaded Convnets for Multilabel Classification of Thoracic Diseases in Chest Radiographs
Pulkit Kumar, Monika Grewal, Muktabh Mayank Srivastava
Chest X-ray is one of the most accessible medical imaging technique for diagnosis of multiple diseases. With the availability of ChestX-ray14, which is a massive dataset of chest X…
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…
Content Based Document Recommender using Deep Learning
Nishant Nikhil, Muktabh Mayank Srivastava
With the recent advancements in information technology there has been a huge surge in amount of data available. But information retrieval technology has not been able to keep up wi…
Testing the limits of unsupervised learning for semantic similarity
Richa Sharma, Muktabh Mayank Srivastava
Semantic Similarity between two sentences can be defined as a way to determine how related or unrelated two sentences are. The task of Semantic Similarity in terms of distributed r…
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…