492 datasets found

The ResMLP-S12 dataset is used for image classification tasks.

Computed Tomography (CT) dataset for contrast phase classification

Tiny-Imagenet is a dataset of 100,000 224x224 color images, each belonging to one of 200 classes.

The USPS dataset consists of 9298 images of handwritten digits 0-9 (10 classes) of 16x16 pixels in gray scale.

The Willow Object Class dataset comprises 304 images gathered from Caltech-256 (Griffin et al., 2007) and Pascal VOC 2007 (Everingham et al., 2007).

The dataset used in this paper is ImageNet and CIFAR-10 for image classification, and Cityscapes for semantic segmentation.

The ImageNet-32 dataset is a subset of the ImageNet dataset, containing 1,281,167 training samples and 50,000 test samples, distributed across 1,000 labels.

Landsat dataset

Land cover change detection dataset for the 2021 IEEE GRSS Data Fusion Contest

The MNIST dataset is a collection of 70,000 28x28 grayscale images of handwritten digits, and the USPS dataset is a collection of 9,298 16x16 grayscale images of handwritten...

The dataset used in the paper to evaluate the alignment of deep neural networks with human perception.

The SMMNIST dataset is an extension of the MNIST dataset, where the digit images form a temporal sequence, creating dynamic scenes as a result of random movements of the...

The dataset used in the paper is a collection of images of objects with varying viewpoints, used for training and testing the proposed RRB framework.

Customer temporal behavioral data represented as images to perform churn prediction by leveraging deep learning architectures prominent in image classification.

The MNIST dataset is used for image classification, and the Lending Club Loan dataset is used for tabular data.

The dataset used in the paper is LeNet, a convolutional neural network for image classification.

The inaturalist species classification and detection dataset contains images of 8,142 species.

Long-tailed classification has been extensively studied in recent years due to its importance in real-world applications with heavily imbalanced data distribution.

The Street View House Numbers (SVHN) dataset used consist of 32x32 10,000 labelled image pool, 30,000 unlabelled pool and 26,032 testing pool.

UAVid is a dataset for semantic segmentation of UAV images, containing 420 images with 8 classes.