660 datasets found

The Office-10 dataset is a more classic benchmark dataset from [17].

The ImageCLEF-DA1 dataset is also a benchmark dataset for domain adaptation, which contains 12 categories shared by three public datasets, Caltech- 256 (C), ImageNet ILSVRC 2012...

The Office-31 dataset is a standard benchmark for domain adaptation from [16], comprising 4,652 images and 31 categories collected from three distinct domains: Amazon (A), Webcam...

The proposed method is evaluated on a toy example problem of sequence counting followed by MNIST classification problem.

The Cars dataset is a multi-object multi-camera network application.

The CGQA dataset is a large dataset containing 413 attributes and 674 object categories.

The MNIST dataset is a large dataset of handwritten digits, and the Temporal MNIST dataset is a variant of MNIST where similar inputs are put together.

The MNIST digits dataset used in the one-shot learning experiments.

The CIFAR-10 and Vggface2 datasets are used for image classification and face recognition tasks.

The dataset used in the WaveAttack paper, which consists of four classical benchmark datasets: CIFAR-10, CIFAR-100, GTSRB, and a subset of ImageNet.

The dataset used in the paper is ImageNet 642, a large-scale image classification dataset.

The dataset used in the paper is ImageNet 322, a large-scale image classification dataset.

A dataset of 5207 beer bottle images and brand labels was created for the challenge of the master course Deep Learning.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Google Cloud Vision platform to test their attack.

A synthetic dataset of blobs in 2D space, with different distributions for P and Q.

The dataset used in the paper is MNIST Fashion and MNIST Handwritten digits.

Image classification dataset

Text, tabular and image classification datasets

The MNIST, FMNIST, and CIFAR10 datasets are used to evaluate the proposed methods of spiking-MaxPooling.

Mobile crowdsensing has gained significant attention in recent years and has become a critical paradigm for emerging Internet of Things applications. The sensing devices...