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Colored MNIST dataset
The dataset used in the paper is a binary classification task in a 300-dimensional space. The procedure for generating the training dataset is as follows: Each label y ∈ {−1, 1}... -
Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
MNIST and CIFAR-10
The MNIST dataset is a large dataset of handwritten digits, and the CIFAR-10 dataset is a dataset of images from 10 different classes. -
ImageNet, ADE20K, and COCO datasets
The dataset used for ImageNet recognition, ADE20K semantic segmentation, and COCO panoptic segmentation. -
Open Images Dataset V4
A dataset for image classification, object detection, and visual relationship detection. -
UltraMNIST
UltraMNIST is a synthetic dataset generated by making use of the MNIST digits. For constructing an image, 3-5 digits are sampled such that the total sum of digits is less than 10. -
Salient-Imagenet
The dataset used in the paper is a large-scale dataset Salient-Imagenet, which is based on Imagenet with pixel-level annotations of irrelevant (spurious) and relevant (core)... -
Plant phenotyping
The dataset used in the paper is a real-world dataset for plant phenotyping, where half of the leaf images are infected with a Cercospora Leaf Spot (CLS), which are the black... -
Decoy-MNIST
The dataset used in the paper is a synthetic dataset similar to decoy-MNIST of Ross et al. (2017) with induced shortcuts and is presented in Section 5.2. For evaluation on... -
ImageNet classification
ImageNet classification dataset, COCO dataset -
STL-10 dataset
The dataset used in this paper is a collection of images from the STL-10 dataset, preprocessed and used for training and evaluation of the proposed diffusion spectral entropy... -
MNIST database of handwritten digits
The MNIST handwritten digit database is a dataset of 60,000 training and 10,000 test examples of handwritten digit images. -
ImageNet Large Scale Visual Recognition Challenge (ILSVRC)
The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset is a large-scale image classification dataset containing over 14 million images from 21,841 categories. -
PACS dataset
The dataset used in the paper is a large collection of small images, each representing a patch of a jigsaw puzzle. The patches are of the same size and orientation, and the goal... -
Image dataset
The dataset used in the paper is a set of images, and the authors used it to train and test their ladder network model.