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MNIST data set
The MNIST data set is a dataset used for testing the performance of the DisDF. -
Caltech-UCSD Birds
Caltech-UCSD Birds (CUB 200-2007) and extended version CUB 200-2011 image collections tagged with keypoints, bounding boxes, coarse segmentation, and attribute labels. -
CIFAR-10 and Tiny ImageNet datasets
The CIFAR-10 and Tiny ImageNet datasets are used to evaluate the robustness of the proposed defense method. -
CIFAR-10-C and CIFAR-100-C
CIFAR-10-C and CIFAR-100-C are robustness benchmarks consisting of 19 corruptions types with five levels of severities. -
Imagenette
The Imagenette dataset used in the paper for class density and dataset quality in high-dimensional, unstructured data. -
Scattering Networks for Hybrid Representation Learning
Scattering networks are a class of designed Convolutional Neural Networks (CNNs) with fixed weights. We argue they can serve as generic representations for modeling images. -
rotated MNIST, CIFAR-10, and PatchCamelyon
The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used the rotated MNIST, CIFAR-10, and PatchCamelyon datasets. -
Very Deep Convolutional Networks for Large-Scale Image Recognition
The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category. -
ImageNet trained PyTorch models under various simple image transformations
ImageNet trained PyTorch models are evaluated under various simple image transformations. -
Open Images Dataset
The dataset used in the experiment consists of 50 images equally distributed between five classes: aircraft, bird, bicycle, boat, and dog. Each class has 5 true positive images... -
ResNet and WRN datasets
ResNet and WRN datasets used for image classification tasks -
CIFAR-100 and ImageNet-1k
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CIFAR-100 and ImageNet-1k datasets for image classification and semantic... -
MobileNetV2 dataset
The dataset used in the paper is the MobileNetV2 dataset, which is a pre-trained deep neural network model. -
STL-10 dataset
The dataset used in this paper is a collection of images from the STL-10 dataset, preprocessed and used for training and evaluation of the proposed diffusion spectral entropy... -
ImageNet Large Scale Visual Recognition Challenge (ILSVRC)
The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset is a large-scale image classification dataset containing over 14 million images from 21,841 categories. -
CIFAR-10, CIFAR-100, and Tiny-ImageNet datasets
The CIFAR-10, CIFAR-100, and Tiny-ImageNet datasets used for training and testing the proposed framework. -
PACS dataset
The dataset used in the paper is a large collection of small images, each representing a patch of a jigsaw puzzle. The patches are of the same size and orientation, and the goal...
