Recognition of Table Images Using K Nearest Neighbors and Convolutional Neural Networks

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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