Techniques for deep learning with satellite & aerial imagery

An open source library and framework for deep learning on satellite and aerial imagery.

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

Interactive interface for browsing global, full-resolution satellite imagery

Aerostack2 is a ROS 2 framework developed to create autonomous multi-aerial-robots systems in an easy and powerful way.

Global shoreline mapping tool from satellite imagery

Gridgeist turns product intent into a rigorous visual system—without the generic AI SaaS aftertaste.

An open framework to simulate and deploy perception-based PX4/ArduPilot drone swarms with ROS2, YOLO, LiDAR, NVIDIA Jetson

Photogrammetry Guide. Photogrammetry is widely used for Aerial surveying, Agriculture, Architecture, 3D Games, Robotics, Archaeology, Construction, Emergency management, and Medical.

SAS.Planet is a free, open-source Geographic Information System (GIS) software designed for viewing, downloading, and managing high-resolution satellite imagery and conventional maps from various online sources.

Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery

Aerial Object Detection using a Drone with PX4 Autopilot and ROS 2. PX4 SITL and Gazebo Garden used for Simulation. YOLOv8 used for Object Detection.