Search Results for author:
Found 11 papers, 1 papers with code
PrivPAS: A real time Privacy-Preserving AI System and applied ethics
This motivates us to work towards a solution to generate privacy-conscious cues for raising awareness in smartphone users of any sensitivity in their viewfinder content.
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.
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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Codeswitched Sentence Creation using Dependency Parsing
Codeswitching has become one of the most common occurrences across multilingual speakers of the world, especially in countries like India which encompasses around 23 official languages with the number of bilingual speakers being around 300 million.
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 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.
