120 datasets found

The dataset used in this paper for image annotation, consisting of 4,999 annotated images with a vocabulary of up to 200 keywords.

The ImageNet ILSVRC 2012 validation dataset is used to evaluate the proposed approach.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a combination of datasets from the scikit-learn library and the UCI machine...

A dataset of 26K corn seed images, classified into pure seeds and three other defective classes (broken, silkcut, and discolored).

The gisette dataset is a collection of 20,000 text documents, each containing a single sentence.

The NIPS2017 dataset is a collection of images used for adversarial attacks.

The dataset consists of 2,000 data points for digits 0 to 9.

A synthetic dataset of blobs in 2D space, with different distributions for P and Q.

The dataset used in the paper is MNIST Fashion and MNIST Handwritten digits.

miniImageNet, tieredImageNet, Caltech-USCD birds-200-2011

The Imagenette dataset used in the paper for class density and dataset quality in high-dimensional, unstructured data.

The Tiny-ImageNet dataset is a subset of the ImageNet dataset.

The proposed method aims to utilize the similarity correlation between different instances.

The dataset used in the paper is a benchmark dataset for multi-class image classification: CIFAR-10, CIFAR-100, FashionMNIST, and SVHN.

The dataset used in this paper is a custom dataset generated for fine-tuning open-sourced models.

The BEiT dataset used for the experiments in the paper.

The dataset used for the experiments in the paper, which includes ImageNet, MS COCO, Cityscapes, and ADE20K datasets.

The RSNA 2019 Brain CT Hemorrhage Challenge dataset is a dataset of CT scans of the brain used for hemorrhage detection and classification.

The Caltech-UCSD Birds (CUB) dataset is a fine-grained visual classification dataset containing 200 classes of birds.

ResNest: Split-attention networks.