A Convolutional Neural Network model created using PyTorch library over the MNIST dataset to recognize handwritten digits .
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Updated
Jan 3, 2021 - Python
A Convolutional Neural Network model created using PyTorch library over the MNIST dataset to recognize handwritten digits .
The C++ neural network for handwritten digit recognition with online demo
This task of digit recognition is done using Hidden Markov Model using Speech signal as input. This model is written in C++ and is trained on custom-recorded digit dataset.
a Java project to classify images of digits
This is a project to solve SUDOKU using Computer Vision in python. Digit recognition model is trained on MNIST with accuracy>95%. Learned Machine Learning and Computer vision and implemented the concepts in this project.
Uma interface que permite desenhar um digito e que reconhece o digito utilizando um algoritmo de machine learning.
Digits Recognize with Drawing(HTML Canvas). The Machine Learning Model can recognize any Handwritten Digit.
Digit recognizer with 97.5% accuracy according to the Kagle scoring. I used different algorithms like; SVM, KNN, and Decision Tree
Classification algorithms to identify images by their bitmaps
Implementation of MobileNet-V3 with pytorch and tested with Kaggle MNIST dataset
user-drawn digit recognition program
Reconocedor de Dígitos trazados con el mouse
Digit recognition using Tensorflow.js
MNIST Digit Recognition repository offers a robust solution for recognizing handwritten digits using the MNIST dataset.
This source loads images from file system and train the classifier.
digitRecognition
Mouse drawn live Digit Recognizer using Keras CNN and cv2 canvas
In this Kaggle competition, your goal is to correctly identify digits from a dataset of tens of thousands of handwritten images.
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