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Self-driving perception, LiDAR/camera fusion, trajectory prediction, drone perception, robot manipulation
1,664 datasets
Featuring terrestrial LiDAR (TLS) point cloud data capturing detailed 3D vegetation structure at the Great Western Woodlands SuperSite on Credo Station, Western Australia. It was collected in 2021 by the Terrestrial Ecosystem Research Network (TERN) to support analysis of vegetation dynamics and ecosystem function.
A collection of terrestrial LiDAR point clouds capturing detailed 3D vegetation structure at the Cumberland Plain Woodland SuperSite in Western Sydney, Australia. It was collected in 2022 by the Terrestrial Ecosystem Research Network (TERN) as part of a standardized national monitoring effort.
UNESCO-sourced education indicators for the Islamic Republic of Iran, updated as of March 2026. The dataset aggregates SDG 4 metrics, demographic data, and socio-economic indicators from the UIS bulk data service.
Panocarla is a dataset hosted on HuggingFace by author Soon122. Its title suggests a focus on autonomous vehicle perception, likely combining panoramic imagery and data from the CARLA simulator. The dataset was last updated on May 24, 2026.
August 17, 2021 through September 4, 2021 airborne measurements from the NASA DC-8 aircraft during the CPEX-AW field campaign. The dataset includes GPS positioning, aircraft orientation, and atmospheric state measurements of temperature, pressure, water vapor, and horizontal winds. It was collected by NASA and ESA for post-launch calibration and validation of the ADM-AEOLUS wind Lidar satellite.
From July 17 to 29, 2014, the Fish Lidar, Oceanic, Experimental (FLOE) system collected the first synoptic measurements of subsurface phytoplankton layers in the Arctic Ocean's Marginal Ice Zone. Data was gathered via a series of aircraft flights from Barrow, Alaska, over the Chukchi and Beaufort Seas. The lidar simultaneously measured layer characteristics and fractional ice cover, capturing phenomena not visible to satellites that influence marine productivity and carbon export.
A bilateral air transport agreement between Canada and Pakistan establishes the framework for commercial air services. The archived document is provided by Global Affairs Canada for research and recordkeeping purposes. It was last updated in the platform on February 26, 2026, but the agreement content itself is noted as outdated.
A consolidated list of supervised organizations in Colombia's solidarity sector, including general data, location, and supervision characteristics. The dataset is published by datos.gov.co and was last updated on March 5, 2026. It includes columns for entity name, ID, activity, location, contact details, and supervision status.
An RTK-SLAM dataset for evaluating absolute global positioning accuracy in GNSS-degraded and GNSS-denied environments. The dataset was created by researchers from the Institute for Photogrammetry and Geoinformatics at the University of Stuttgart, Germany, and was last updated in April 2026.
2001 data from the CAMEX-4 field campaign collected by the University of Alabama in Huntsville Mobile Integrated Profiling System (MIPS). This dataset provides measurements from Electric Field Mills, capturing information about atmospheric electrical fields above the instruments. The data is hosted by the Global Hydrology Resource Center Distributed Active Archive Center (GHRC DAAC).
Central Texas coast airborne lidar surveys conducted by the Bureau of Economic Geology, University of Texas at Austin. The dataset includes two surveys from February 27, 2024, and August 1, 2024, capturing conditions before and after Hurricane Beryl made landfall. Data files include LAS point clouds and wrack line shapefiles.
PortWatch provides daily port call counts and shipment volume estimates in metric tons for maritime hubs in the Islamic Republic of Iran. This time-series data tracks both incoming and outgoing trade activity at the port level, with records updated through March 2026.
The dataset comprises behavioral response scores and covariates for Antarctic predators, as described in the 2021 Frontiers in Marine Science publication. It was published by researchers from the National Oceanic and Atmospheric Administration and the Southwest Fisheries Science Center. The data supports a study comparing disturbance from drones versus traditional ground survey methods.
A 5.5 KB dataset from figshare, last updated March 2026, records the impact of chitosan and essential oil treatments on fruit postharvest disease percentage in 'Etmany' cultivar winter guava. The data was collected under controlled cold storage conditions of 8 ± 1°C and 90% relative humidity. It was authored by Assiya Ansabayeva and is shared under a CC-BY-4.0 license.
Cranfield Synthetic Drone Detection is a dataset referenced in the paper 'Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data'. The dataset was uploaded by author 'mazqtpopx' to the Hugging Face platform and was last updated on April 23, —2026. Its specific contents and scale are not detailed in the provided metadata.
CATS-ISS_L1B_D-M7.2-V3-00 is a Cloud-Aerosol Transport System Level 1B data product from NASA. It provides range-resolved vertical profiles of atmospheric aerosols and clouds, collected from the International Space Station between March 25, 2015, and October 29, 2017. The instrument operated at three wavelengths, orbiting between approximately 230 and 270 miles above Earth's surface.
The Data Management and Sharing Plan for the Road2Code project outlines the strategy for managing and sharing scientific data generated for neuro-symbolic program synthesis in autonomous driving scene translation and analysis. The plan was authored by Praneeth Chakravarthula and was last updated on May 4, 2026. It describes the data to be used and generated but does not contain the actual dataset files.
Monthly conflict forecasts for Iran generated by the Violence & Impacts Early-Warning System (VIEWS) consortium. The data provides predictive insights into violent conflict and fatalities up to 36 months in advance, with the most recent update recorded in March 2026.
Topobathymetric data merges land topography and water depth into a single product for inundation mapping. The dataset was developed using U.S. Geological Survey topography and NOAA bathymetry, with high-resolution NASA EAARL lidar data for nearshore areas. These data were collected under the USGS Gulf of Mexico Integrated Science Tampa Bay Study.
G-LiHT's portable airborne system simultaneously maps forest composition, structure, and function across North America. Data products include LiDAR-derived visualizations of elevation above bare earth, such as Digital Surface Model, Mean, Aspect, Rugosity, and Slope layers. These raster products are provided at a nominal 1-meter spatial resolution over targeted areas in the Conterminous United States, Alaska, Puerto Rico, and Mexico.