40 Open Source Mnist Classification Software Projects
Free and open source mnist classification code projects including engines, APIs, generators, and tools.
Digital Image Processing36 ⭐
My works for EE 569 - Digital Image Processing - Spring 2018 - Graduate Coursework at USC - Dr. C.-C. Jay Kuo
Mi Lad Snip69 ⭐
Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.
Pytorch Adversarial Training175 ⭐
PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.
Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning
Mnist Classification178 ⭐
This dataset has 10 food categories, with 5,000 images. For each class, 125 manually reviewed test images are provided as well as 375 training images. All images were rescaled to have a maximum side length of 512 pixels.
Mlp Training For Mnist Classification14 ⭐
Multilayer perceptron deep neural network with feedforward and back-propagation for MNIST image classification using NumPy
Compression algorithms (like the well-known zip file compression) can be used for machine learning purposes, specifically for classifying hand-written digits (MNIST)
Pytorch Classification Uncertainty135 ⭐
This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"
Official Implementation of "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics" (ICML 2021)
Dedhiaparth98 Capsule Network12 ⭐
A TensorFlow implementation of Capsule Network as described in the paper Dynamic Routing Between Capsules
MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.
Handwritten Digit Recognition Using Deep Learning137 ⭐
Handwritten Digit Recognition using Machine Learning and Deep Learning
Tensorflow Mnist Mlp Batch_normalization Weight_initializers48 ⭐
MNIST classification using Multi-Layer Perceptron (MLP) with 2 hidden layers. Some weight-initializers and batch-normalization are implemented.
Tensorflow Mnist Cnn189 ⭐
MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
Android TensorFlow MachineLearning MNIST Example (Building Model with TensorFlow for Android)
Mnist Android Tensorflow332 ⭐
Handwritten digits classification from MNIST with TensorFlow on Android; Featuring Tutorial!