525 datasets found

The dataset used in this paper is a convolutional neural network (CNN) model, specifically ConvNeXt.

The dataset used in this paper is a convolutional neural network (CNN) model, specifically ResNet-34, and its layers 20 and 28.

The VGG-9 dataset is a popular benchmark for image classification tasks.

The dataset used in this paper is a large-scale neural network model, specifically a ResNet-VAE model, trained on the CIFAR-10 dataset.

The dataset used in the paper is MNIST, Fashion MNIST, and CIFAR-10.

The MOON dataset is used to test the proposed TEMP-based spiking neural network.

The 3s vs 7s MNIST problem is a classic dataset in machine learning. It consists of 28x28 grayscale images of handwritten digits, with 3s and 7s in the images.

Xception: A deep neural network architecture for image classification and segmentation.

The dataset used for the proposed MoCo-SAS framework, which consists of high-resolution Synthetic Aperture Sonar (SAS) data.

Caltech-UCSD Birds (CUB 200-2007) and extended version CUB 200-2011 image collections tagged with keypoints, bounding boxes, coarse segmentation, and attribute labels.

The Patch Camelyon dataset is a dataset of 1,000 images of 2 classes.

The dataset used in the paper is a collection of trained networks and their corresponding datasets.

The MNIST and ResNet50 datasets are used to test the onnx-mlir compiler.

The dataset used in the paper is CIFAR-10, CIFAR-100, and Tiny-Imagenet.

The dataset used in the paper is a subset of the Caltech Silhouettes database, consisting of 11 images with 42 to 59 pixels in each class.

The Oxford 102 Category Flower dataset consists of 8,189 images with 102 categories of flowers which commonly occurs in the United Kingdom, and each category has 40 to 258 images.

The dataset used in the paper is a classification dataset, specifically CIFAR-100 and CUB200.

The RESISC-45 dataset is a benchmark for remote sensing image classification.

The CIFAR-10 and Tiny ImageNet datasets are used to evaluate the robustness of the proposed defense method.

The dataset used in the paper is the ImageNet-2k dataset, a large dataset for image classification.