492 datasets found

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, and ImageNet datasets.

Pre-trained language models (PrLM) have to carefully manage input units when training on a very large text with a vocabulary consisting of millions of words. Previous works have...

The Microsoft COCO dataset was used for training and evaluating the CNNs because it has become a standard benchmark for testing algorithms aimed at scene understanding and...

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...

The dataset used in the paper is the ImageNet-21k dataset, which is a large-scale hierarchical image database.

The dataset used in this paper is a notMNIST dataset, which is a binary image dataset.

The dataset used in this paper is a Caltech-101 dataset, which is a dataset of images.

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...

The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CLIP model and the CIFAR-10 and ImageNet datasets.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...