A Deep CNN Model for Student Learning Pedagogy Detection Data Collection Using OCR

Student learning pedagogy detection requires a huge amount of data from students. Efficient process to collect the data is a major fact here. This paper proposes an approach based on Convolutional Neural Network (CNN) for Optical Character Recognition (OCR) and mainly shows a method to use this OCR system to extract information of a student filled in a specialized form. This form contains 170 cells. Some of these cells are to be filled with capital English alphabets and others are to be filled with English numerals. This paper discusses a method for feature extraction and use of CNN to identify each cell. Using this method we could predict 96.87% of numeric data and 94.36% of alphabetic data accurately.