MNIST 42000 images Computer Vision Project
Updated 2 years ago
Description
The MNIST database (Modified National Institute of Standards and Technology database) is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning. It was created by "re-mixing" the samples from NIST's original datasets. The creators felt that since NIST's training dataset was taken from American Census Bureau employees, while the testing dataset was taken from American high school students, it was not well-suited for machine learning experiments. Furthermore, the black and white images from NIST were normalized to fit into a 28x28 pixel bounding box and anti-aliased, which introduced grayscale levels.
Yann LeCun, Courant Institute, NYU Corinna Cortes, Google Labs, New York Christopher J.C. Burges, Microsoft Research, Redmond
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
mnist-42000-images-u0qdg_dataset,
title = { MNIST 42000 images Dataset },
type = { Open Source Dataset },
author = { Roboflow },
howpublished = { \url{ https://universe.roboflow.com/roboflow-jvuqo/mnist-42000-images-u0qdg } },
url = { https://universe.roboflow.com/roboflow-jvuqo/mnist-42000-images-u0qdg },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { apr },
note = { visited on 2025-07-16 },
}