You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This project offers an efficient method for identifying and recognizing handwritten text from images. Using a Convolutional Recurrent Neural Network (CRNN) for Optical Character Recognition (OCR), it effectively extracts text from images, aiding in the digitization of handwritten documents and automated text extraction.
Using a Convolutional Neural Network (CNN) to identify the Kannada numerical digits. Tensorflow (Keras) is used to create, train and load the neural network model. CustomTKinter/TKinter are used to provide the GUI and OpenCV is used to read input form the GUI.
Implemented various Machine Learning and Deep Learning Algorithms on the famous digit recognition problem using the MNIST (Mixed National Institute of Standards and Technology) database.
A digit recognition canvas where you can draw your own custom digits on the canvas and the program will predict what digit it thinks it is using a neural network.
An app that recognizes handwritten digits, either through an in-built canvas or through a photo of a handwritten digit (on paper) taken by the camera and outputs the respective number using a Machine Learning algorithm (Neural Network) via text and voice.