CamelinaWeed brings together field UAV imagery, orthomosaic products, and expert agronomist annotations from real Camelina sativa fields in Northern Greece. The dataset captures weeds under different seasons, locations, flight heights, sensors, and crop growth conditions, providing polygon-level labels for broad weed groups and species-level categories. It also includes raw RGB and multispectral imagery for orthomosaic reconstruction, together with ready-to-use RGB and multispectral GeoTIFF orthomosaics for field-scale analysis.
DroneWaste targets automated identification of waste materials from drone-derived orthomosaics, supporting environmental inspection workflows. Each visible waste instance is annotated with a segmentation mask, bounding box, and category mapped to the European Waste Code (EWC).
CoFly-WeedDB includes expert agronomist annotations for three common weed species (Johnson grass, field bindweed, purslane) and is suitable for training segmentation models in precision agriculture.
A benchmark dataset built from real 3PL operations. It provides privacy-preserving matrices (no raw addresses) and richly structured constraints to test VRP solvers and learning-based routing.
BaleUAVision provides large-scale, field-diverse aerial imagery of hay bale fields with human annotations and multiple annotation formats (COCO/YOLO/CSV/JSON/masks), plus orthomosaics to support mapping and simulation workflows.