Dataset Card for CIFAR 10 Table of Contents Dataset Description Dataset Summary Supported Tasks and Leaderboards Languages Dataset Structure Data Instances Data Fields Data Splits Dataset Creation Curation Rationale Source Data Annotations Personal and Sensitive Information Considerations for Using the Data Social Impact of Dataset Discussion of Biases Other Known Limitations Additional Information Dataset Curators Licensing Information Citation Information Contributions Dataset Description Homepage: https://www.cs.toronto.edu/~kriz/cifar.html Repository: Paper: Learning Multiple Layers of Features from Tiny Images by Alex Krizhevsky Leaderboard: Point of Contact: Dataset Summary The CIFAR 10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain more images from one class than another. Between them, the training batches…
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