Number Recognition of Parts Book Schematics using Convolutional Recurrent Neural Network

OCR (Optical Character Recognition) has been becoming a vital method to recognize digits, letters, symbols and so on. The main idea is basically the conversion of data files which consists of handwritten or machine-written digits or characters into a type to let the machine make edits and read. This way, it lets computers read articles or books. They can also read images and make the conversion to a text file by using OCR. There are two important benefits of OCR. First, is the enhancement of the device to operate more productively even if the number of employees is decreased. Secondly, is the increase in the efficiency of the storage. This paper compares two state-of-the-art OCR algorithms in a simulated environment by using modified dataset. Simulation results are shown in part 4.