This is a synthetic dataset built to benchmark the capabilities of explainable AI methods against difficult tasks. The dataset has two classes, which depend on whether there is an odd or an even n
MNIST is a classic dataset consisting of 0~9 handwritten digit images and labels, which provides 60,000 pieces of training data and 10,000 pieces of testing data
This is a subset of ImageNet called "ImageNet16" more suited for cases with limited computational budget and faster experimentation. Each class has 400 train images and 100 test images. * Credit al
Tiny ImageNet contains 100000 images of 200 classes (500 for each class) downsized to 64 x 64 colored images. Each class has 500 training images, 50 validation images, and 50 test images. The dataset