492 datasets found

The ImageCLEF-DA1 dataset is also a benchmark dataset for domain adaptation, which contains 12 categories shared by three public datasets, Caltech- 256 (C), ImageNet ILSVRC 2012...

The Office-31 dataset is a standard benchmark for domain adaptation from [16], comprising 4,652 images and 31 categories collected from three distinct domains: Amazon (A), Webcam...

The CGQA dataset is a large dataset containing 413 attributes and 674 object categories.

Pascal Visual Object Classification challenge consist of 20 image classes, where each image was parsed into an image graph using keypoints as nodes.

The CIFAR-10 and Vggface2 datasets are used for image classification and face recognition tasks.

The dataset used in the WaveAttack paper, which consists of four classical benchmark datasets: CIFAR-10, CIFAR-100, GTSRB, and a subset of ImageNet.

The dataset used in the paper is ImageNet 642, a large-scale image classification dataset.

The dataset used in the paper is ImageNet 322, a large-scale image classification dataset.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Google Cloud Vision platform to test their attack.

Image classification dataset

Text, tabular and image classification datasets

The MNIST, FMNIST, and CIFAR10 datasets are used to evaluate the proposed methods of spiking-MaxPooling.

Mobile crowdsensing has gained significant attention in recent years and has become a critical paradigm for emerging Internet of Things applications. The sensing devices...

Dataset bias is a significant problem in training fair classifiers. When attributes unrelated to classification exhibit strong biases towards certain classes, classifiers...

The dataset used in the paper is the ImageNet 2012 dataset.

MiniImageNet, TieredImageNet, and CUB are used for few-shot learning tasks.

XIMAGENET-12 is an explainable visual benchmark dataset for model robustness evaluation. It consists of over 200K images with 15,410 manual semantic annotations. The dataset is...

Typical deep neural network (DNN) backdoor at-

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

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