minst-database
There are 15 repositories under minst-database topic.
hlatourette/nn-handwriting
Handwriting detection using neural networks
Code-MonkeyZhang/miniflow
miniflow is a deep learning framework built from scratch using Python and NumPy, mimicking the TensorFlow API format.
simone-rizzo/MINST-NN-and-CNN-models
Creating models for MINST database: NN and CNN
cyruscyliu/DigitalRecognition
Course project of IMAGE PROCESSING in BIT
muddukrishna96/MNIST_datasets_projects
The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image. It is a good database for people who want to try learning techniques and pattern recognition methods on real-world data while spending minimal efforts on preprocessing and formatting. This repository contain projects made using the MNIST dataset
Vvkmnn/ganDL
🖌️ An image generating neural network via Tensorflow.
costagreg/mnist-handwritten-ml
Machine Learning that recognise numbers from 0 to 9 from a HTML canvas! Built in TensorFlow 1.3
ff-zhang/mnist-classifier
SGD classifier for the MINST dataset built using Eigen in C++
VMunhangane/CIFO_PROJECT_Breaking-CNNs-MNIST-Dataset_Oreo_Group
Breaking CNNs – MNIST Dataset_Oreo_Group: In this report it is going to be shown the effect of GA by creating adversarial examples. These images are going to be created using MNIST dataset. The test dataset is going to be evolved using the main operators of GA and the goal is to make CNN model classify images incorrectly.
ahoucbvtw/Minst-Pratice
Minst pratice
AllanOtieno254/mnist-digit-classification
building a machine learning model to classify handwritten digits using the MNIST dataset.
Boggartfly/TensorFlow-Python-Neural-Network-Example
Working example of the example program described on the TensorFlow MINST Pro Tutorial
sa-artea/TallerML-GAN-CGAN-DISC
Taller de ML (Aprendizaje de Máquina) para crear imágenes artĂsticas (Generative Art) con redes Adversarias Generadoras y Condicionadas (GAN/CGAN) con los datos MINST de moda (Fashion MINST).