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

6 citations · 38 across the 12 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.CL2020★ 1 cited

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…

cs.CL2020★ 3 cited

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…

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★ 5 cited

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…

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…