6 citations · 38 across the 12 of their papers we have counts for
15 papers
On-Device Spatial Attention based Sequence Learning Approach for Scene Text Script Identification
Rutika Moharir, Arun D Prabhu, Sukumar Moharana +2
Automatic identification of script is an essential component of a multilingual OCR engine. In this paper, we present an efficient, lightweight, real-time and on-device spatial atte…
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…
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…
STRIDE : Scene Text Recognition In-Device
Rachit S Munjal, Arun D Prabhu, Nikhil Arora +2
Optical Character Recognition (OCR) systems have been widely used in various applications for extracting semantic information from images. To give the user more control over their…
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…
TeLCoS: OnDevice Text Localization with Clustering of Script
Rachit S Munjal, Manoj Goyal, Rutika Moharir +1
Recent research in the field of text localization in a resource constrained environment has made extensive use of deep neural networks. Scene text localization and recognition on l…
On-Device Tag Generation for Unstructured Text
Manish Chugani, Shubham Vatsal, Gopi Ramena +2
With the overwhelming transition to smart phones, storing important information in the form of unstructured text has become habitual to users of mobile devices. From grocery lists…
On-Device Sentence Similarity for SMS Dataset
Arun D Prabhu, Nikhil Arora, Shubham Vatsal +3
Determining the sentence similarity between Short Message Service (SMS) texts/sentences plays a significant role in mobile device industry. Gauging the similarity between SMS data…
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…
On-Device Language Identification of Text in Images using Diacritic Characters
Shubham Vatsal, Nikhil Arora, Gopi Ramena +4
Diacritic characters can be considered as a unique set of characters providing us with adequate and significant clue in identifying a given language with considerably high accuracy…
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…
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…
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)…
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…
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…