preprintarXiv (Cornell University)Aug 25, 2017GREEN OA

Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

XHXiao, HanKRKashif RasulRVRoland Vollgraf
Indexed inarxivdatacite

Abstract

We present Fashion-MNIST, a new dataset comprising of 28x28 grayscale images of 70,000 fashion products from 10 categories, with 7,000 images per category. The training set has 60,000 images and the test set has 10,000 images. Fashion-MNIST is intended to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms, as it shares the same image size, data format and the structure of training and testing splits. The dataset is freely available at https://github.com/zalandoresearch/fashion-mnist

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6,068
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3

Topics & keywords

Keywords
  • MNIST database
  • Benchmarking
  • Artificial intelligence
  • Grayscale
  • Computer science
  • Set (abstract data type)
  • Test set
  • Pattern recognition (psychology)
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