Popular GitHub Repositories for Recognising Digits

Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.

M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4.

A free audio dataset of spoken digits. An audio version of MNIST.

Using spiking neurons and spike-timing-dependent plasticity to classify the MNIST handwritten digits.

In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits

Vanilla neural network implemented in all major languages

A simple JavaScript neural network framework.

Predict handwritten digits with CoreML

A simple, easy to use MNIST loader written in Python 3

? A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.

A simple Flask application that recognizes handwritten digits. Developed using TensorFlow and Keras.

Neural network library written in C and Javascript

A collection of some cool deep learning projects in python

Digits detection with YOLOv8 detection model and ONNX pre/post processing

Handwritten Number Recognition using CNN and Character Segmentation

Generative Adversarial Network that learns to generate handwritten digits. (Learning Purposes)

Emerging Technologies Project - 4th Year 2017

Unlock the potential of latent diffusion models with MNIST! ? Dive into reconstructing and generating digits using cutting-edge techniques like Autoencoders with Channel Attention Blocks and DDPMs. Perfect for enthusiasts of computer vision, deep learning, and generative modeling! ??

A deep learning based application which is entitled to help the visually impaired people. The application automatically generates the textual description of what's happening in front of the camera and conveys it to person through audio. It is capable of recognising faces and tell user whether a known person is standing in front of him or not.

Android application recognizing digits using quantized 8-bit MobileNetV3.