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ImageNet and SST2 datasets
The dataset used in this study for image and text classification tasks. -
ImageNet ILSVRC 2012 validation dataset
The ImageNet ILSVRC 2012 validation dataset is used to evaluate the proposed approach. -
DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information ...
Deluge Networks are deep neural networks which efficiently facilitate massive cross-layer information inflows from preceding layers to succeeding layers. -
NITI: INTEGER TRAINING
The dataset used in this paper is MNIST, CIFAR10, and ImageNet. -
CIFAR-10, CIFAR-100, ImageNet, and their out-of-distribution variants
The dataset used in the paper is CIFAR-10 and CIFAR-100, ImageNet, and their out-of-distribution variants. -
A Comprehensive Evaluation Framework for Deep Model Robustness
Deep neural networks (DNNs) have achieved remarkable performance across a wide range of applications, while they are vulnerable to adversarial examples, which motivates the... -
ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framew...
ILMPQ: An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA -
Lifelong-CIFAR10 and Lifelong-ImageNet
Lifelong-CIFAR10 and Lifelong-ImageNet are ever-expanding pools of test samples designed to enhance the robustness of current benchmarks by mitigating the issue of overfitting... -
Shen fMRI dataset
fMRI dataset for model training: The fMRI data originates from Shen et al. (2019). This Shen fMRI dataset recorded human brain fMRI signals from three subjects while they... -
NAS-Bench-301 and AlphaNet
The dataset used in the paper is NAS-Bench-301 and AlphaNet. NAS-Bench-301 is a surrogate NAS benchmark built via deep ensembles and modeling uncertainty, which provides... -
MNIST and ImageNet datasets
The MNIST dataset is a large dataset of handwritten digits, and the ImageNet dataset is a large dataset of images. -
ImageNet and YouTube-8M
The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used datasets such as ImageNet and YouTube-8M. -
CIFAR-10, CIFAR-100, GTSRB, ImageNet
The dataset used in the WaveAttack paper, which consists of four classical benchmark datasets: CIFAR-10, CIFAR-100, GTSRB, and a subset of ImageNet. -
ImageNet 642
The dataset used in the paper is ImageNet 642, a large-scale image classification dataset. -
ImageNet 322
The dataset used in the paper is ImageNet 322, a large-scale image classification dataset. -
ImageNet 2012 dataset
The dataset used in the paper is the ImageNet 2012 dataset. -
Imagenette
The Imagenette dataset used in the paper for class density and dataset quality in high-dimensional, unstructured data. -
ImageNet Subsets
ImageNet Subsets -
ImageNet and CC-3M datasets
ImageNet [9] and CC-3M [43] datasets -
Frequency Centric Defense Mechanisms against Adversarial Examples
The proposed work uses the magnitude and phase of the Fourier Spectrum and the entropy of the image to defend against Adversarial Examples.
