mnistShort017: A short version of the MNIST data set

In curveDepth: Tukey Curve Depth and Distance in the Space of Curves

Description

First 100 digits from the MNIST data set belonging to classes '0', '1', and '7' representable as curves agter skeletonization.

Usage

data("mnistShort017")

Format

A list of three elements '0', '1', and '7', each being an array with dimensions (28, 28, 100). Each slice of each of these arrays, in third dimension, contains a single monochrome digit image represented by a 28x28 indicator matrix. See Lafaye De Micheaux, Mozharovksyi and Vimond (2018) and accompanying codes for details on preprocessing.

Author(s)

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

preprocessing performed by Myriam Vimond (CREST, Ensai, University of Bretagne Loire).

Source

http://yann.lecun.com/exdb/mnist/

References

LeCun, Y., Bottou, L.,Bengio, Y., and Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278-2324.

Lafaye De Micheaux, P., Mozharovskyi, P. and Vimond, M. (2018). Depth for curve data and applications.

curveDepth documentation built on May 1, 2019, 8 p.m.