117 datasets found

The Grassy-MNIST dataset is a semi-synthetic dataset of hand-written digits from the MNIST dataset superimposed on images of grass from the ImageNet dataset.

The dataset used in the paper is ImageNet and Wiki103.

The dataset used in the paper is ImageNet + ResNet101 and WT103 + TransformerXL models.

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...

The dataset used in the experiment was the ImageNet ILSVRC2012 dataset [24]. It has 1,000 classes and about 1.2 million total images.

The dataset used in this paper is CIFAR-10 and ImageNet datasets.

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.

The dataset used in the paper for few-shot classification tasks, including ImageNet, ImageNetV2, ImageNet-Sketch, ImageNet-A, ImageNet-R.

CIFAR-10 32x32, ImageNet 64x64, FFHQ 64x64, and AFHQ-v2 64x64 datasets.

The dataset used for evaluating the Variable Length Embeddings (VLE) model, consisting of a mix of the iNaturalist and ImageNet datasets.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used four widely used datasets: CIFAR10, CIFAR100, SVHN, and ImageNet.

The dataset used in the paper is the ImageNet-1K and ImageNet-22K datasets.

The dataset used in the paper is the CIFAR-100 and ImageNet datasets.

The dataset used in the paper is ImageNet with pre-trained VGG16 model.

The dataset used in the paper is a large set of real images extracted from various object categories of the ImageNet, COCO, and Unpaired real dataset.

The dataset used in the paper Strike (with) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects. The dataset consists of 30 unique 3D object models...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the NeurIPS'17 adversarial competition dataset, compatible with ImageNet,...

The dataset used for classification is ImageNet2012 (ImageNet) from [33] and Intel Image Classification (Natural Scene) from [18].

The dataset used in the paper is the ImageNet validation set, a subset of the ImageNet dataset.

This paper uses the ImageNet and COCO2017 validation datasets for testing.