MNIST Benchmark Database

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An MNIST Benchmark Database is an annotated database of handwritten digit images.



References

2012

  • (Deng, 2012) ⇒ Li Deng. (2012). “The MNIST Database of Handwritten Digit Images for Machine Learning Research [best of the Web].” IEEE Signal Processing Magazine 29, no. 6
    • QUOTE: ... this issue ... presents the modified National Institute of Standards and Technology (MNIST) resources, consisting of a collection of handwritten digit images used extensively in optical character recognition and machine learning research …

1998a

1998b

  • (LeCun et al., 1998b) ⇒ Yann LeCun, Corinna Cortes, and Christopher J.C. Burges. (2010). “MNIST Handwritten Digit Database.” AT&T Labs [Online]. Available: http://yann.lecun.com/exdb/mnist 2
    • QUOTE: 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. …

      … The original black and white (bilevel) images from NIST were size normalized to fit in a 20x20 pixel box while preserving their aspect ratio. The resulting images contain grey levels as a result of the anti-aliasing technique used by the normalization algorithm. the images were centered in a 28x28 image by computing the center of mass of the pixels, and translating the image so as to position this point at the center of the 28x28 field.