492 datasets found

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

The PASCAL Visual Object Classes Challenge (VOC) is a benchmark dataset for object detection and semantic segmentation.

The CIFAR-FS dataset is a few-shot learning dataset, consisting of 60,000 color images from 100 classes with 600 examples per class.

The dataset used in the paper is a de-noising diffusion probabilistic model (DDPM) trained on CIFAR-10, CIFAR-100, STL-10, and Tiny-ImageNet.

The dataset used in the paper is a collection of images from FashionMNIST, CIFAR10, CIFAR100, and STL10 datasets.

A neural network with single-hidden layer of 64 hidden units and ReLU activations. A prior precision of ε = 1, a minibatch size of 128 and 16 Monte-Carlo samples are used for...

The PASCAL VOC dataset contains 20 classes, including person, animal, vehicle, and indoor, with 9,963 images containing 24,640 annotated objects.

The dataset used in the paper is a modified version of CIFAR10 and CIFAR100 datasets, subsampled to create irregularly scattered nodes for each image.

The masked classes dataset is a subset of the ImageNet dataset, where some class labels are masked.

The binned classes dataset is a subset of the ImageNet dataset, divided into bins based on class labels.

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

The Caltech-UCSD Birds-200-2011 Dataset consists of 11,169 bird images from 200 categories and each category has 60 images averagely.

Maps dataset is a dataset of maps images, containing 10,000 images with 10 categories.

The dataset is used for testing the proposed GE-ViT model.

The dataset is used for testing the proposed GE-ViT model.

The NIH Chest X-ray dataset contains over 100,000 frontal-view X-ray images.

The ImageNet 2012 dataset is used to evaluate the performance of the proposed neural network decoupling approach on large-scale image classification tasks.

Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in...

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

The COCO dataset is a large-scale dataset for object detection and image classification.