The Global Wheat Full Semantic Organ Segmentation (GWFSS) Dataset

2025 · Arvalis

Computer vision is increasingly used in farmers' fields and agricultural experiments to quantify important traits related to crop performance. In particular, imaging setups with a sub-millimeter ground sampling distance enable the detection and tracking of plant features, including size, shape and color. While today's AI-driven foundation models segment almost any object in an image, they still fail to perform effectively for complex plant canopies. To improve model performance for wheat, the global wheat dataset consortium assembled a large and diverse set of images from research experiments around the globe. After the success of the global wheat head detection dataset (GWHD), the new dataset targets a full semantic segmentation (GWFSS) of wheat organs (leaves, stems and spikes).

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• Projet : Programme transversal 2024 « Mobilisation du levier du numérique pour soutenir la conception, le pilotage, le déploiement et la valorisation de systèmes de production agricole innovants et performants »

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