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Image classification, object detection, segmentation, face recognition, OCR, image generation, video understanding
15,976 datasets
Statistics Canada provides survey data on businesses that changed marketing practices to promote Canadian products over a 12-month period. The dataset is organized by industry classification, business size, type, activity, and ownership. Data was released for the first quarter of 2026.
First quarter 2026 survey data from Statistics Canada on measures businesses find most effective for increasing purchases or sales across Canadian provinces or territories. It categorizes responses by industry classification (NAICS), business size, type, activity, and ownership structure. The data was published by Statistics Canada on February 27, 2026.
Statistics Canada data measures how businesses passed tariff-related cost increases to customers during the first quarter of 2026. It categorizes responses by NAICS industry, business employment size, type of business, activity, and majority ownership. The dataset was published by Statistics Canada in February 2026.
Statistics Canada surveyed businesses on actions taken over a 12-month period due to U.S. tariffs on Canadian imports. The data is disaggregated by NAICS industry classification, business size, type, activity, and majority ownership. This official survey was published in the first quarter of 2026.
Statistics Canada collected business expectations on changes in supply chain challenges for the first quarter of 2026. The data is segmented by industry classification (NAICS), business size, type of business, activity, and majority ownership. It was published on February 27, 2026.
Statistics Canada collected survey data on changes in supply chain challenges for businesses and organizations during the first quarter of 2026. The dataset categorizes responses by North American Industry Classification System (NAICS) code, business employment size, type of business, business activity, and majority ownership. It was published by Statistics Canada in February 2026.
Canadian business expectations for the duration of supply chain obstacles in the first quarter of 2026. The dataset is segmented by industry classification, business size, type of business, business activity, and majority ownership. It was published by Statistics Canada on February 27, 2026.
First quarter of 2026 survey data from Statistics Canada details the most challenging obstacles expected by Canadian businesses over the next three months. Responses are categorized by North American Industry Classification System (NAICS) codes, business employment size, type of business, activity, and majority ownership. The dataset was published by Statistics Canada in February 2026.
Survey data details obstacles expected by Canadian businesses and organizations over a three-month period. The dataset is categorized by North American Industry Classification System (NAICS), business employment size, type of business, activity, and majority ownership. It was published by Statistics Canada for the first quarter of 2026.
Statistics Canada surveyed business expectations over a three-month horizon for the first quarter of 2026. The data is categorized by NAICS industry code, business size, type of business, activity, and majority ownership. This official survey was last updated in February 2026.
An image dataset for detecting diseases on olive leaves. The dataset is published on Kaggle and likely contains images annotated for use with the YOLO object detection framework. The title suggests the collection may include augmented and rare disease samples.
A model checkpoint file for an image generation system, likely related to anime or visual novel art styles. It is hosted on the Kaggle platform. The specific architecture, training data, and performance characteristics are not detailed in the provided metadata.
IDD-YOLO-FORMAT is a dataset hosted on Kaggle. The title suggests it is formatted for the YOLO object detection framework, likely derived from the Indian Driving Dataset. The dataset's specific contents, such as the number of images or annotations, are not detailed in the available metadata.
A dataset titled 'my-cnn-code' published on Kaggle. The title suggests it contains code related to Convolutional Neural Networks. The dataset's specific content, size, and authorship are unknown from the provided metadata.
A selection of images and short animations explaining key aspects of the 2004 Indian Ocean/Sumatra tsunami, revised and issued for release on the tenth anniversary of the disaster. The resources were updated from existing materials previously released by Geoscience Australia. The dataset includes files in MP4, PDF, and HTML formats.
3.3 million hiring organizations are represented in this dataset tracking daily US job listing volume. Data is derived from online job listings, capturing an average of 70% of all new US jobs, and published nightly. The dataset provides 7-day averages of new listings, expressed as a percentage of the baseline from March 1, 2020.
Worldwide satellite broadcasts of aviation weather information, a joint effort by ICAO, the U.S. FAA, NOAA/NWS, and other international partners. The system has been operational since 1996, with data archived at the National Climatic Data Center since 2002. It delivers global forecasts of temperature, winds, and humidity, with data transfer speeds significantly faster than previous systems.
The German Wadden Sea region, from the dike line to the 10-meter isobath, is covered by this environmental database. The WATiS system consolidates data from 42 research projects on sedimentology, biology, pollutants, meteorology, hydrology, and topography to facilitate information exchange among research groups and administrative agencies. A central database (WADABA) maintains consistency, with interfaces to GIS and other database systems.
A 1987 geospatial database digitized from the Atlas of Uganda (1964 and 1967 editions) by UNEP/GRID-Nairobi with support from Ugandan experts. It contains layers for climatology, geomorphology, animals, boundaries, land cover, population, and land use, though some layers are noted as outdated. Datasets are in Transverse Mercator Projection with coordinates stored in Latitude/Longitude.
The PRIRODA MSU-SK Sensors Data and Products contain infrared and visible imagery registered by the Multispectral Scanners with Conical Scanning (MSU-SK) instrument aboard the PRIRODA module of the Mir space station. The dataset includes six spectral channels across visible, near-infrared, and infrared bands, with spatial resolutions ranging from 60x144 meters to 120x570 meters. It was collected as part of an international remote sensing program involving participants from multiple countries, including the United States, Russia, and European nations.