Tools tagged with "Foundation Models"

Terratorch is an open-source Python toolkit developed by terrastackai. It provides essential functionalities and tools for researchers and developers to fine-tune Geospatial Foundation Models (GFMs), adapting them to specific tasks and datasets. This platform facilitates advanced machine learning applications within the geospatial domain.

GeoIntel is an open-source project leveraging Google's Gemini API for advanced geo-location analysis. It focuses on using artificial intelligence to accurately determine the precise geographic location where a photograph was originally captured. This tool provides capabilities for uncovering hidden spatial data within image metadata.

This Python package is designed for segmenting geospatial data, integrating the Segment Anything Model (SAM) to bring advanced AI-driven computer vision to the geospatial domain. It enables efficient identification and delineation of objects or regions within various raster datasets, including satellite imagery and aerial photos.

This GitHub repository provides a comprehensive, curated list of academic papers dedicated to geospatial embeddings. It explores various methods for representing Earth data—spatial, temporal, and semantic—within embedding spaces, examining their behavior and applications. The collection aims to be a valuable resource for researchers and practitioners interested in the intersection of machine learning and geospatial science.

GeoSpy is an AI-powered visual intelligence platform designed for precise photo geolocation, transforming images into actionable intelligence. It serves enterprise and law enforcement agencies by identifying locations from photos with high accuracy, even without metadata. The tool is vital for investigations, OSINT, and rapidly determining where photos were taken.

Delineate Anything is a cutting-edge foundation model designed for the precise delineation of field boundaries from satellite imagery. It offers resolution-agnostic capabilities, allowing for effective application across various image resolutions. This project aims to provide a robust solution for automated agricultural field mapping and analysis.

Ai2, founded by Paul Allen, conducts high-impact research and engineering to tackle key problems in artificial intelligence. This institute focuses on developing and providing open models, applications for science and the environment, and advancing AI research.

Development Seed focuses on improving planetary observation through robust cloud infrastructure for managing vast geospatial data. The company applies artificial intelligence to solve environmental challenges and designs user-centric geo-data products for actionable insights.

The CNG Blog is the official blog of the Cloud-Native Geospatial Forum, a community dedicated to advancing cloud-native geospatial practices. It features articles on new technologies, community sprints, technical developments, and expert insights.