19,997 machine learning datasets
19,997 dataset results
Topical subsets of WikiData, assembled using the WikiDataSets python library. Extracted from Wikidata in April 2020.
Wiki-en is an annotated English dataset for domain detection extracted from Wikipedia. It includes texts from 7 different domains: “Business and Commerce” (BUS), “Government and Politics” (GOV), “Physical and Mental Health” (HEA), “Law and Order” (LAW), “Lifestyle” (LIF), “Military” (MIL), and “General Purpose” (GEN).
The Wiki-Flick Event dataset for cross-modal event retrieval is a well-labelled but weakly-aligned dataset collected for cross-modality event retrieval. The dataset consists of 28,825 images on Flickr and 11,960 text articles from hundreds of social media, belonging to 82 categories of events.
A publicly available set of question and sentence pairs, collected and annotated for research on open-domain question answering.
The goal of this dataset is to understand how people experience sexism and sexual harassment in the workplace by discovering themes in 2,362 experiences posted on the Everyday Sexism Project's website
A balanced dataset of color names and RGB values for training classifiers.
The X-MARS dataset proposes new splits for the MARS dataset, to allow for cross-evaluation with the Market-1501 dataset without training and test overlap between the two datasets.
Collections of images of the same rotating plastic object made in X-ray and visible spectra. Both parts of the dataset contain 400 images. The images are maid every 0.5 degrees of the object axial rotation. The collection of images is designed for evaluation of the performance of circular motion estimation algorithms as well as for the study of X-ray nature influence on the image analysis algorithms such as keypoints detection and description.
The Humbug Zooinverse dataset is a dataset of mosquito audio recordings. With over a thousand contributors, it contains 195,434 labels of two second duration, of which approximately 10 percent signify mosquito events.
A more balanced version of ZuBuD.
The data consists of a set of 3 task types and 4 question types, creating 12 total scenarios. The tasks are grouped into stories, which are denoted by the numbering at the start of each line.
Gutenberg Poem Dataset is used for the next verse prediction component.
The Kite database is a multi-modal dataset for the control of unmanned aerial vehicles (UAVs). There are three modalities present in the dataset:
COCO Earthquake is a dataset similar to Common Objects in Context (COCO) used for cracking segmentation. The images selected in the dataset are at various scales, and the tool referred to as the COCO Annotator is used to label cracks for training. In these labeled images, cracks are in yellow and background is in purple. Size of the training and labeling images is varied from 168×300 to 4600×3070. By excluding steel structures, 2,021 images are labeled when surface cracks appeared on structural or nonstructural materials at various scales.
VLUC (Video-Like Urban Computing) is a benchmark for video-like computing on citywide traffic density and crowd prediction. It consists of two new datasets BousaiTYO and BousaiOSA and existing datasets TaxiBJ, BikeNYC I-II, and TaxiNYC.
InstaCities1M is a dataset of social media images with associated text. It consists of Instagram images associated associated with one of the 10 most populated English speaking cities all over the world. It has 100K images for each city, which makes a total of 1M images, split in 800K training images, 50K validation images and 150K testing images. All images were resized to 300x300 pixels.
The Part-Whole Relations dataset is a dataset of semantic relations between entities. It contains the following subtypes: - Component-Of - Member-Of - Portion-Of - Stuff-Of - Located-In - Contained-In - Phase-Of - Participates-In
Visual Choice of Plausible Alternatives (VCOPA) is an evaluation dataset containing 380 VCOPA questions and over 1K images with various topics, which is amenable to automatic evaluation, and present the performance of baseline reasoning approaches as initial benchmarks for future systems.
The LWIR DoFP Dataset of Road Scene (LDDRS) is a road detection dataset with 2,113 annotated images. It contains both day and night scenes, with multiple cars and pedestrians per image.
Cross Modal Automatic Commenting (CMAC) is a task which aims to automatically generate comments for graphic news. The CMAC dataset is a large-scale dataset for this task which consists of 24,134 graphic news. Each instance is composed of several news photos, news title, news body, and corresponding high-quality comments.