660 datasets found

The Fifteen Natural Scene Categories database is used for bag-of-features based image classification problem.

UT Zappos50K dataset

A variant of CIFAR-100 dataset, where the original dataset is split into 20 disjoint tasks, each consisting of 2,500 samples from 5 classes.

The dataset used in the paper is FashionMNIST and CIFAR-10, which are commonly used datasets for image classification tasks.

The dataset used in this study for image and text classification tasks.

A dataset used for testing the proposed Deep Feature Learning method for histopathology image classification.

A dataset used for training and testing the proposed Deep Feature Learning method for histopathology image classification.

A dataset composed of 35334 breast histopathology images at zoom x5 (1.76 µm per pixel) distributed amongst 23 imbalanced classes, which include both common tumor and benign...

A dataset of 3000 images collected on a public roadway for front seat vehicle occupancy detection.

The dataset used in this paper for image annotation, consisting of 4,999 annotated images with a vocabulary of up to 200 keywords.

Two datasets used for multi-task learning, CIFAR-100 and AGNews.

The dataset used in the paper is the ImageNet noise dataset, which contains 60,000 32x32 color images with random labels.

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

The ImageNet ILSVRC 2012 validation dataset is used to evaluate the proposed approach.

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.

A dataset from 500px, an online photography website, containing 225,922 users and 300,000 photos.

The dataset used in the paper for hyper-parameter tuning using transient cloud resources.

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.