Английская Википедия:Fashion MNIST

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Шаблон:Short description

The Fashion MNIST dataset is a large freely available database of fashion images that is commonly used for training and testing various machine learning systems.[1][2] Fashion-MNIST was intended to serve as a replacement for the original MNIST database for benchmarking machine learning algorithms, as it shares the same image size, data format and the structure of training and testing splits.[3]

The dataset contains 70,000 28x28 grayscale images of fashion products from 10 categories from a dataset of Zalando article images, with 7,000 images per category.[1] The training set consists of 60,000 images and the test set consists of 10,000 images. The dataset is commonly included in standard machine learning libraries.[4]

History

The set of images in the Fashion MNIST database was created in 2017 to pose a more challenging classification task than the simple MNIST digits data, which saw performance reaching upwards of 99.7%.[1]

The GitHub repository has collected over 4000 stars and is referred to more than 400 repositories, 1000 commits and 7000 code snippets.[5]

Numerous machine learning algorithms[6] have used the dataset as a benchmark,[7][8][9][10] with the top algorithm[11] achieving 96.91% accuracy in 2020 according to the benchmark rankings website.[12] The dataset was also used as a benchmark in the 2018 Science paper using all optical hardware to classify images at the speed of light.[13] Google, University of Cambridge, IBM Research, Université de Montréal, and Peking University are the repositories most published institutions as of 2021.Шаблон:Citation needed

See also

References

Шаблон:Reflist

External links

Шаблон:Differentiable computing Шаблон:Standard test item