660 datasets found

The Imagenette dataset is a zero-shot image classification dataset, containing 13,394 images from ten easily separable classes in ImageNet.

The dataset used in this paper is a synthetic dataset with a nonlinear response, where the response is learned by means of a neural network trained to count numbers in synthetic...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used ImageNet and several famous super-resolution image datasets.

The EMNIST Balanced dataset is a large collection of images of handwritten characters.

The Caltech-256 object category dataset is used for the feature extraction step, and the Omniglot dataset is used for the evaluation.

The PASCAL VOC2007 dataset is a benchmark for object detection and image classification.

The dataset used in this paper is CIFAR-10/100 and Imagenette datasets.

The dataset used in the paper is ImageNet-1K and MS COCO.

The proposed SAOL improves the performances of representative architectures for various tasks, with almost the same computational cost. Moreover, additional self-supervision...

The dataset used in the paper is a remote sensing image classification dataset, which includes five optical remote sensing (RS) image classification benchmarks.

The paper presents a method for reading digits in natural images using unsupervised feature learning.

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

The dataset used in this paper is CIFAR-10, CelebA-HQ, LSUN-Church and LSUN-Bedrooms.

The dataset used in the paper is Cifar-10 and TinyImagenet.

The dataset used in the paper is a set of images from the AFHQ dataset, containing 1.5K images of different animal faces.

The dataset used in the paper is ImageNet, MS COCO, and Pascal VOC datasets.

The dataset used in the paper is a subset of the CIFAR-100 dataset, consisting of 10,000 training samples randomly sampled from CIFAR-100's training samples corresponding to the...

The dataset used in this paper for classification tasks on spherical-MNIST, atomic energy, Shrec17 data sets, and group testing on diffusion MRI data.

The RSNA-MICCAI brain tumor radiogenomic classification challenge dataset is a dataset for predicting MGMT biomarker status in glioblastoma using mpMRI scans.

The MNIST dataset is a large dataset of handwritten digits, and the Fashion MNIST dataset is a similar dataset but with different styles.