Upload of the corrupted version of Tiny ImageNet (also known as ImageNet-200) with fixed frost-corrupted samples (see https://github.com/hendrycks/robustness/issues/60). This version can be downloaded on a server (for instance using TorchUncertainty) and is safer than the original mirror on berkeley connect (that may soon be deleted). Original work by Dan Hendrycks & Thomas Dietterich under the Apache-2.0 license. If you consider this dataset useful, please cite: @article{hendrycks2019robustness, title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations}, author={Dan Hendrycks and Thomas Dietterich}, journal={Proceedings of the International Conference on Learning Representations}, year={2019} }I am not...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
This repository contains the Tiny ImageNet-C and Tiny ImageNet-P dataset from Benchmarking Neural Ne...
This repository contains the Tiny ImageNet-C and Tiny ImageNet-P dataset from Benchmarking Neural Ne...
This repository contains the Tiny ImageNet-C and Tiny ImageNet-P dataset from Benchmarking Neural Ne...
This repository contains the ImageNet-P dataset from Benchmarking Neural Network Robustness to Commo...
This repository contains the ImageNet-C dataset from Benchmarking Neural Network Robustness to Commo...
Adversarial patches are optimized contiguous pixel blocks in an input image that cause a machine-lea...
Adversarial patches are optimized contiguous pixel blocks in an input image that cause a machine-lea...
This repository contains the CIFAR-100-C dataset from Benchmarking Neural Network Robustness to Comm...
This repository contains the CIFAR-10-C and CIFAR-10-P dataset from Benchmarking Neural Network Robu...
Benchmarking the robustness to distribution shifts traditionally relies on dataset collection which ...
We introduce several new datasets namely ImageNet-A/O and ImageNet-R as well as a synthetic environm...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
This repository contains the Tiny ImageNet-C and Tiny ImageNet-P dataset from Benchmarking Neural Ne...
This repository contains the Tiny ImageNet-C and Tiny ImageNet-P dataset from Benchmarking Neural Ne...
This repository contains the Tiny ImageNet-C and Tiny ImageNet-P dataset from Benchmarking Neural Ne...
This repository contains the ImageNet-P dataset from Benchmarking Neural Network Robustness to Commo...
This repository contains the ImageNet-C dataset from Benchmarking Neural Network Robustness to Commo...
Adversarial patches are optimized contiguous pixel blocks in an input image that cause a machine-lea...
Adversarial patches are optimized contiguous pixel blocks in an input image that cause a machine-lea...
This repository contains the CIFAR-100-C dataset from Benchmarking Neural Network Robustness to Comm...
This repository contains the CIFAR-10-C and CIFAR-10-P dataset from Benchmarking Neural Network Robu...
Benchmarking the robustness to distribution shifts traditionally relies on dataset collection which ...
We introduce several new datasets namely ImageNet-A/O and ImageNet-R as well as a synthetic environm...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...
Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not seen dur...