activity
20192021
most citedOn-Device Information Extraction from SMS using Hybrid Hierarchical Classification

6 citations · 24 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2021★ 1 cited

A Simple Approach to Image Tilt Correction with Self-Attention MobileNet for Smartphones

Siddhant Garg, Debi Prasanna Mohanty, Siva Prasad Thota +1

The main contributions of our work are two-fold. First, we present a Self-Attention MobileNet, called SA-MobileNet Network that can model long-range dependencies between the image…

cs.CV2021

On-Device Content Moderation

Anchal Pandey, Sukumar Moharana, Debi Prasanna Mohanty +3

With the advent of internet, not safe for work(NSFW) content moderation is a major problem today. Since,smartphones are now part of daily life of billions of people,it becomes even…

cs.CV2021

ScreenSeg: On-Device Screenshot Layout Analysis

Manoj Goyal, Rachit S Munjal, Sukumar Moharana +3

We propose a novel end-to-end solution that performs a Hierarchical Layout Analysis of screenshots and document images on resource constrained devices like mobilephones. Our approa…

cs.CV2020★ 4 cited

On-Device Text Image Super Resolution

Dhruval Jain, Arun D Prabhu, Gopi Ramena +4

Recent research on super-resolution (SR) has witnessed major developments with the advancements of deep convolutional neural networks. There is a need for information extraction fr…

cs.CV2020

On-device Filtering of Social Media Images for Efficient Storage

Dhruval Jain, DP Mohanty, Sanjeev Roy +2

Artificially crafted images such as memes, seasonal greetings, etc are flooding the social media platforms today. These eventually start occupying a lot of internal memory of smart…

cs.CL2020★ 6 cited

On-Device Information Extraction from SMS using Hybrid Hierarchical Classification

Shubham Vatsal, Naresh Purre, Sukumar Moharana +2

Cluttering of SMS inbox is one of the serious problems that users today face in the digital world where every online login, transaction, along with promotions generate multiple SMS…

cs.CL2020★ 5 cited

An Efficient Architecture for Predicting the Case of Characters using Sequence Models

Gopi Ramena, Divija Nagaraju, Sukumar Moharana +2

The dearth of clean textual data often acts as a bottleneck in several natural language processing applications. The data available often lacks proper case (uppercase or lowercase)…

cs.CV2020★ 5 cited

On- Device Information Extraction from Screenshots in form of tags

Sumit Kumar, Gopi Ramena, Manoj Goyal +4

We propose a method to make mobile screenshots easily searchable. In this paper, we present the workflow in which we: 1) preprocessed a collection of screenshots, 2) identified scr…

cs.IR2019★ 3 cited

On-Device User Intent Prediction for Context and Sequence Aware Recommendation

Benu Madhab Changmai, Divija Nagaraju, Debi Prasanna Mohanty +3

The pursuit of improved accuracy in recommender systems has led to the incorporation of user context. Context-aware recommender systems typically handle large amounts of data which…