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ImageNet Large Scale Visual Recognition Challenge
A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a... -
MNIST Dataset
The MNIST dataset (Lecun et al., 1998), which consists of 60,000 gray-scale images of handwritten digits. Each image has an accompanying label in {0, 1,..., 9}, and is stored as... -
Learning Multiple Layers of Features from Tiny Images
The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.