I made a real time Sudoku solver using the camera, it looks for the edges of the Sudoku in the frame, extracts it, solves it and overlays the solution on the puzzle itself. For the digit recognition, I used a CNN, trained using Keras with printed characters from the different ubuntu fonts. For the image processing part, I used OpenCV for the edge detection.

This project shows how to use CNN to perform Chinese character recognition, a much more complicated task compared to MNIST digit recognition.

This CNN-based model for recognition of hand written digits attains a validation accuracy of 99.2% after training for 12 epochs. Its trained on the MNIST dataset on Kaggle.

Handwritten Digit Recognition WebApp using pytorch and Flask

Zynq/FPGA实现CNN手写数字(0-9)识别

Implementing CNN for Digit Recognition (MNIST and SVHN dataset) using PyTorch C++ API

A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.

A CNN-based hardware digit/image recognition module designed on PyTorch and then implemented with Verilog on FPGA

Multiple Handwritten Digit Recognition app Using Deep Learing - CNN from Canvas build on tkinter- GUI

Handwritten Digit Recognition using OpenCV, Keras, CNN

A Convolutional Neural Network model created using PyTorch library over the MNIST dataset to recognize handwritten digits .

The training dataset consists of 42000 rows each of 784 pixel values thus representing 28 x 28 sized 42000 images of different digits from 0 to 9 . I have used Convolutional Neural Networks to train the model with the help of Keras and made predictions on the 28000 images of the test dataset, also achieved 99.321 % valid accuracy with just 10 epochs . Also tuned ImageDataGenerator to promote generalization and avoid overfitting problem .

【Framework】This is a captcha recognition algorithm tailored for 4 length digit recognition. Written in CNN, Tensorflow 1.3-1.7.

ASL alphabet and digits recognition from human gestures and gesture controlled calculator Using CNN-Keras-tensorflow.

基于CNN的手写数字识别(使用MNIST数据集)

Digits and Capital Alphabets recognition using cnn with tensorflow

This is an example code of a CNN for MNIST handwritten digit recognition with Unity Tensorflow at runtime.

jupyter notebook for mnist digit recognition using CNN, CNN feature map visualization and facical expression recognition

Automatically recognize handwritten digits from photos. Handwritten digits recognition by CNN and SVM.

This project is a handwriting recognition system using a convolutional neural network (CNN) based on TensorFlow and Keras. It can recognise handwritten digits and also allows users to draw digits on a canvas for real-time recognition.

Digit Recognition using CNN and TensorFlow

This is the code I created to find solutions to the Kaggle MNIST digit recognition competition using a Convolutional Neural Network.

[Keras|OpenCV|Flask] Implemented a numerical calculator by digit and symbol recognition on handwritten images. Build and trained a CNN model on Kaggle’s Handwritten math symbols Dataset using Keras in Python and OpenCV for pre-processing the input image. The model can recognize digits, arithmetic and relational operators.

This project focuses on recognising string of handwritten digits inputed as an image

Renewal/Churn probability prediction of Telecom Customers, CNN- Handwritten Digit recognition

Utilize OpenMP and CUDA to speed up LeNet-5 digit recognition CNN. In OpneMP, training with 11x speed up and 11x in testing. With the help of CUDA, the training is speed up by 3x and 57x speed up in testing.

A Handwritten Equation Solver built using Convolutional Neural Network and Optical Character Recognition. CNN model is used for recognition of digits and symbols. OCR is used for processing the the image and segmentation.

MNIST Handwritten Digit Classification and Recognition Using Convolutional Neural Network (CNN) Deep Learning

Digit Recognition Project Using CNN (PYTHON)

Recognition of single digits written in air using a deep learning-based convolutional neural network (CNN) approach.