8 datasets found

The use of machine learning for remote sensing has matured alongside an increase in the availability and resolution of satellite imagery, enabling advances in such tasks as land...

The use of machine learning for remote sensing has matured alongside an increase in the availability and resolution of satellite imagery, enabling advances in such tasks as land...

Geospatial datasets are diverse, naturally spatiotemporal, and inherently multimodal (composed of two or more distinct signal types or modalities) e.g., satellite/aerial imagery...

A dataset of wildfire incidence rates within the continental United States.

Machine learning in remote sensing has matured alongside an increase in the availability and resolution of satellite imagery, enabling advances in such tasks as land use...

T-Drive trajectory data sample. https://www.microsoft.com/en-us/research/publication/t-drive-trajectory-data-sample/, 2011.

CRM and HCRM are computed in diverse geographical areas from probe data [9].

Probe data is similar to GPS trajectories found in publicly available datasets such as [7, 8]. More details of this proprietary and privacy-preserving dataset can be found in...