Hemavathi P.

Work place: Bangalore Institute of Technology (VTU), Bengaluru, Karnataka, India

E-mail: hemavathibitcse09@gmail.com


Research Interests: Models of Computation, Data Structures and Algorithms, Computer Networks, Artificial Intelligence, Wireless Networks, Computational Science and Engineering


Dr. Hemavathi P is an assistant professor in the department of Computer Science and Engineering, Bangalore Institute of Technology, Bengaluru, Karnataka, India. She has obtained PhD, M.Tech and B.E from Jain University, Dr. Ambedkar Institute of Technology Bangalore, (VTU), Manipal Institute of Technology, Manipal (University of MAHE), respectively. She is having 16 years of experience as an academician. She has published various journals and conferences of national and international repute. Her area of interest includes Wireless networks, Internet of Things, Artificial Intelligence and Machine Learning.

Author Articles
Analog Document Search Using CRNN and Keyphrase Extraction

By Lokeshwar S Vadiraja Rao M. K Sujay Kumar P. S Vishveshwara Guthal Gowda Hemavathi P.

DOI: https://doi.org/10.5815/ijigsp.2021.02.02, Pub. Date: 8 Apr. 2021

There seems to be a peculiar trend in the way information is now used, moving to digital media not just for the newspapers but for books as well. With advances in Optical Character Recognition (OCR), Style Transfer Mapping (STM), and efficient key phrasing, we are now able to digitalize the document to a form that can be read across multiple platforms and searched efficiently. It provides users with the ease of searching for relevant documents without the tedious process of manual searching.
We propose a system that uses the CRNN model to detect English characters in the document with high accuracy. We then pair it with a hybrid keyphrasing technique, which uses Positional Rank as its Graph based rank and re-rank the key phrases using the C-Value method. This process allows us to automatically digitize the printed document and summarise it to provide high-quality keyphrases, which can be used to efficiently search and retrieve relevant printed documents.

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