Abstract
The objective of this research paper is to analyze images of tables and build a prediction system capable of recognizing the number of rows and columns of the table image with the help of Convolutional Neural Networks and K Nearest Neighbours. The data set used in the building of the models has been indigenously created and converted to gray-scale. The eventual objective and possible application of the paper is to assist the building of software capable of reading tables from non digital sources and creating digital copies of them.
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Puri, U., Tewari, A., Katyal, S., Garg, B. (2018). Recognition of Table Images Using K Nearest Neighbors and Convolutional Neural Networks. In: Omatu, S., Rodríguez, S., Villarrubia, G., Faria, P., Sitek, P., Prieto, J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol 620. Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_40
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DOI: https://doi.org/10.1007/978-3-319-62410-5_40
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