45 datasets found

The MNIST data set is a dataset used for testing the performance of the DisDF.

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 dataset used in the paper is a modified version of the MNIST dataset, where each image is flipped horizontally or vertically, and the labels are changed accordingly.

The Imagenette dataset used in the paper for class density and dataset quality in high-dimensional, unstructured data.

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.

Semantic segmentation is a fundamental task in computer vision and enables many downstream applications. It is related to image classification since it produces per-pixel...

The dataset used in the paper is ImageNet1K and ImageNet21K for image classification, and MS COCO for object detection.

Places205 is a dataset of 2.5 million images from 205 categories, with 12,000 images per category.

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...

The dataset used in the paper is not explicitly mentioned, but it is implied to be ImageNet and CIFAR-10/100.

Machine learning in remote sensing has matured alongside an increase in the availability and resolution of satellite imagery, enabling advances in such tasks as land use...

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...

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.

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...

Dataset bias is a significant problem in training fair classifiers. When attributes unrelated to classification exhibit strong biases towards certain classes, classifiers...

VisionLLaMA is a unified and generic modeling framework for solving most vision tasks.

The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.

The dataset used in the paper is Places, a large dataset of 400k pairs of images from the Places 205 dataset and corresponding spoken audio captions.

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

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