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MNIST

Classification

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MNIST Computer Vision Project

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70000 images
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THE MNIST DATABASE of handwritten digits

Authors:

  • Yann LeCun, Courant Institute, NYU
  • Corinna Cortes, Google Labs, New York
  • Christopher J.C. Burges, Microsoft Research, Redmond

Dataset Obtained From: http://yann.lecun.com/exdb/mnist/

All images were sized 28x28 in the original dataset

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.

Version 1 (original-images_trainSetSplitBy80_20):

  • Original, raw images, with the train set split to provide 80% of its images to the training set and 20% of its images to the validation set
  • Trained from Roboflow Classification Model's ImageNet training checkpoint

Version 2 (original-images_ModifiedClasses_trainSetSplitBy80_20):

  • Original, raw images, with the train set split to provide 80% of its images to the training set and 20% of its images to the validation set
  • Modify Classes, a Roboflow preprocessing feature, was employed to change class names from 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 to one, two, three, four, five, six, seven, eight, nine
  • Trained from the Roboflow Classification Model's ImageNet training checkpoint

Version 3 (original-images_Original-MNIST-Splits):

  • Original images, with the original splits for MNIST: train (86% of images - 60,000 images) set and test (14% of images - 10,000 images) set only.
  • This version was not trained

Citation:

@article{lecun2010mnist,
  title={MNIST handwritten digit database},
  author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
  journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
  volume={2},
  year={2010}
}

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Last Updated

2 years ago

Project Type

Classification

Subject

digits

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Downloads: 165

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License

CC BY 4.0

Classes

0 1 2 3 4 5 6 7 8 9
ORC
Handwritten-Digits
598 images
0-1-2-3-4-5-6-7-8-9-y5dn
251 images
Digits-Classification
694 images