STL-10 (Self-Taught Learning 10)

Introduced by Adam Coates et al. in An Analysis of Single-Layer Networks in Unsupervised Feature Learning

The STL-10 is an image dataset derived from ImageNet and popularly used to evaluate algorithms of unsupervised feature learning or self-taught learning. Besides 100,000 unlabeled images, it contains 13,000 labeled images from 10 object classes (such as birds, cats, trucks), among which 5,000 images are partitioned for training while the remaining 8,000 images for testing. All the images are color images with 96×96 pixels in size.

Source: Unsupervised Feature Learning with C-SVDDNet


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