660 datasets found

Groups: Image Classification Organizations: No Organization

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  • CG-MNIST

    The CG-MNIST dataset is a synthetic dataset based on MNIST, consisting of 60,000 sample pairs of gray-scale images and monochromatic images.

  • CIFAR10, CIFAR100, and SVHN

    CIFAR10, CIFAR100, and SVHN datasets

  • DeiT-Base

    The dataset used in the paper is also used for training and evaluation of the proposed method.

  • MobileNet-V1

    The dataset used in the paper is also used for training and evaluation of the proposed method.

  • MNIST and USPS

    The MNIST and USPS datasets are used for binary classification tasks.

  • CUB 200-2011

    The CUB 200-2011 dataset contains 200 classes of bird species in 11,788 images with approximately 30 examples per class in the training set.

  • CIFAR-10 and STL-10

    The dataset used in the paper is CIFAR-10 and STL-10, which are commonly used datasets for image classification tasks.

  • ResNet-18

    Training neural networks on image datasets generally require extensive experimentation to find the optimal learning rate regime.

  • CIFAR-100 and ImageNet

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

  • Cifar-10

    A binary imbalanced classification dataset with 32 × 32 color images of 10 classes of natural objects.

  • Fashion-Mnist

    A binary imbalanced classification dataset with 28 × 28 grayscale images of 10 classes corresponding to fashion products.

  • Mnist

    A binary imbalanced classification dataset with 28 × 28 grayscale images of 10 classes corresponding to digits from 0 to 9.

  • ImageNet-Dogs

    The dataset used in the paper for image classification, object detection, and face verification tasks.

  • ImageNet-10

    ImageNet-10 is a dataset of 10,000 224x224 color images in 10 classes, with 1,000 images per class.

  • CIFAR10 and CIFAR100 datasets

    The CIFAR10 and CIFAR100 datasets are used to evaluate the proposed randomized defense method.

  • CIFAR10 and ImageNet Datasets

    CIFAR10 and ImageNet datasets are used as the original task for the pre-trained models.

  • Dynamic Batch Norm Statistics Update for Natural Robustness

    CIFAR10-C and ImageNet-C datasets are used to evaluate the proposed framework for improving the natural robustness of trained DNNs against corrupted inputs.

  • Imagenet

    The dataset used in the paper is the Imagenet dataset, which is a large annotated dataset of images used for image classification tasks.

  • Synthetic Data

    The dataset used in the paper is a synthetic dataset for off-policy contextual bandits, with contexts x ∈ X, a finite set of actions A, and bounded real rewards r ∈ A → [0, 1].

  • Spawrious

    The Spawrious dataset is a synthetic image classification dataset containing images of four dog breeds (classes) in six background locations (spurious attributes).