117 datasets found

The dataset used for image classification and semantic image segmentation.

The ImageNet-1k dataset is used as the backbone network for the proposed DEYOv2 model.

Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and...

The dataset used in the paper is ImageNet V2, a large-scale image classification dataset.

The ILSVRC 2012 classification challenge dataset was used to evaluate the proposed method.

A dataset interface for the ImageNet dataset, allowing for the generation of counterfactual examples that exhibit a specified shift.

The dataset used in the paper is the ResNet-50 dataset, a convolutional neural network model.

Deep convolutional neural networks have achieved remarkable success in computer vision. However, deep neural networks require large computing resources to achieve high...

The dataset used in this paper is ImageNet-1000 pre-trained CNNs.

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

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

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

The dataset used in the paper is the ImageNet 2012 Large-Scale Visual Recognition Challenge dataset.

The dataset used in the paper is the ImageNet dataset for image classification and the CACD dataset for face identification.

The dataset used in the paper is CIFAR-10, Imagenette, and ImageNet.

The dataset used in the TextMesh paper, containing 35 text prompts for 3D mesh generation.

The dataset used in this paper is CIFAR10/100, ImageNet, and CUB-200.

Out-of-distribution (OOD) detection is a crucial task for ensuring the reliability and safety of deep learning. The dataset used in this paper is CIFAR10, CIFAR100, and ImageNet.

The Imagenette dataset is a zero-shot image classification dataset, containing 13,394 images from ten easily separable classes in ImageNet.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used ImageNet and several famous super-resolution image datasets.