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Found 15 papers, 0 papers with code
On-Device Spatial Attention based Sequence Learning Approach for Scene Text Script Identification
Combining the spatial attention mechanism with the residue convolutional blocks, we are able to enhance the performance of the baseline CNN to build an end-to-end trainable network for script identification.
A Simple Approach to Image Tilt Correction with Self-Attention MobileNet for Smartphones
With the combination of our novel approach and the architecture, we present state-of-the-art results on detecting the image tilt angle on mobile devices as compared to the MobileNetV3 model.
On-Device Content Moderation
In addition to conventional porno-graphic content moderation, we have also included semi-nudecontent moderation as it is still NSFW in a large demography. We have curated a dataset comprising of three major categories, namely nude, semi-nude and safe images.
STRIDE : Scene Text Recognition In-Device
We deploy the system on-device with an inference speed of 2. 44 ms per word on the Exynos 990 chipset device and achieve an accuracy of 88. 4\% on ICDAR-13 dataset.
Optical Character Recognition
Optical Character Recognition (OCR)
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TeLCoS: OnDevice Text Localization with Clustering of Script
This makes script identification an overhead in the recognition pipeline.
ScreenSeg: On-Device Screenshot Layout Analysis
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.
On-Device Tag Generation for Unstructured Text
With the overwhelming transition to smart phones, storing important information in the form of unstructured text has become habitual to users of mobile devices.
On-Device Sentence Similarity for SMS Dataset
Determining the sentence similarity between Short Message Service (SMS) texts/sentences plays a significant role in mobile device industry.
On-Device Text Image Super Resolution
Recent research on super-resolution (SR) has witnessed major developments with the advancements of deep convolutional neural networks.
On-Device Language Identification of Text in Images using Diacritic Characters
In this proposed work, we aim to identify language of text in images using the presence of diacritic characters in order to improve Optical Character Recognition (OCR) performance in any given automated environment.
On-device Filtering of Social Media Images for Efficient Storage
Artificially crafted images such as memes, seasonal greetings, etc are flooding the social media platforms today.
On-Device Information Extraction from SMS using Hybrid Hierarchical Classification
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
Since truecasing acts as a preprocessing step in several applications, every increment in the F1 score leads to a significant improvement in the language processing tasks.
On- Device Information Extraction from Screenshots in form of tags
We propose a method to make mobile screenshots easily searchable.
On-Device User Intent Prediction for Context and Sequence Aware Recommendation
Through a neighborhood searching method followed by a sequence matching algorithm, we search for the most relevant node to make the prediction.
