81 datasets found

MPI3D is a benchmark dataset that consists of 1,036,800 examples of 3D objects from three different domains: Toy, RealisticC, and Real.

The dataset is used for deep hashing network for unsupervised domain adaptation.

Test time adaptation (TTA) aims to adapt deep neural networks when receiving out of distribution test domain samples.

The NIST-SRE 2016 dataset contains recordings of speakers from different domains.

A popular dataset for computer vision, where the first domain contains the original images, and the second is generated by applying brightness, gray scaling, and Gaussian blurring.

Jointly measured observations of single-cell RNA-seq and ATAC-seq data.

One domain consists of the original MNIST digits, while the other is generated by applying multiple transformations including rotation, downscaling, and Gaussian blurring.

The data collection process of a given phenomenon may be affected by different sources of variability, creating seemingly distinct domains.

Multi-domain data is becoming increasingly common and presents both challenges and opportunities in the data science community. The integration of distinct data-views can be...

Wearable Human Activity Recognition (WHAR) models usually face performance degradation on the new user due to user variance. Unsupervised domain adaptation (UDA) becomes the...

This paper presents DADLNet, a dynamic domain adaptation based deep learning network framework for decoding motor imagery tasks.

Land cover maps are a pivotal element in a wide range of Earth Observation (EO) applications. However, annotating large datasets to develop supervised systems for remote sensing...

The ImageCLEF-DA dataset is a benchmark dataset for ImageCLEF 2014 domain adaptation challenges, which contains 12 categories shared by three domains: Caltech-256 (C), ImageNet...

A semi-self-supervised domain adaptation technique based on deep convolutional neural networks with a probabilistic diffusion process, requiring minimal manual data annotation.

The dataset used in the paper is the dSprites dataset, which contains 2D-shape binary images with a size of 64×64, synthetically generated with five independent factors: shape...

The Domain Adaptation with Geometric Preservation and Distribution Alignment (DAGDA) dataset is a dataset for domain adaptation with geometric preservation and distribution...

The Conditional Adversarial Domain Adaptation (CADAN) dataset is a dataset for conditional adversarial domain adaptation.

The dataset used in the paper is Office-Home, DomainNet, CUB, and iWildCAM2020.

The MIMIC-CXR dataset is currently the largest radiology imaging dataset available. It comprises a total of 473,057 chest X-ray images and 206,563 associated radiology...

The FMoW dataset aims to classify utility types from satellite images.