Digit Recognition
The purpose of this project is to take handwritten digits as input, process the digits, train the neural network algorithm with the processed data, to recognize the pattern and successfully identify the test digits. The popular MNIST dataset is used for the training and testing purposes. The IDE used is MATLAB
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Qmnist | 227 | 2 years ago | other | Python | ||||||
| The QMNIST dataset | ||||||||||
| Assignment2 2018 | 111 | 6 years ago | Python | |||||||
| (Spring 2018) Assignment 2: Graph Executor with TVM | ||||||||||
| Deepconcolic | 85 | 3 years ago | 2 | bsd-3-clause | Python | |||||
| Concolic Testing for Deep Neural Networks | ||||||||||
| Capsnet_tensorflow | 70 | 6 years ago | 3 | mit | Python | |||||
| How Far Can We Go With Mnist | 59 | 7 years ago | ||||||||
| A collection of codes for 'how far can we go with MNIST' challenge | ||||||||||
| Assignment2 2017 | 59 | 7 years ago | Python | |||||||
| (Spring 2017) Assignment 2: GPU Executor | ||||||||||
| Sadl | 30 | 3 years ago | 2 | mit | Python | |||||
| Code release of a paper "Guiding Deep Learning System Testing using Surprise Adequacy" | ||||||||||
| Tensorflow Mnist | 25 | 7 years ago | Python | |||||||
| MNIST with TensorFlow | ||||||||||
| Convert Own Data To Mnist Format | 23 | 5 years ago | 4 | mit | Python | |||||
| This project is convert own data to MNIST format. It may help you to quickly test new DL model without modify too much code. | ||||||||||
| Neural Network Mnist Cpp | 18 | 9 years ago | C++ | |||||||
| Neural Network implementation in C++ running for MNIST database. | ||||||||||
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Mnist