Détection non supervisée des adventices par drone : résultats et limites

6533b85bfe1ef96bd12bb295

RESEARCH PRODUCT

Détection non supervisée des adventices par drone : résultats et limites

Gawain Jones Marine Louargant Sylvain Villette Jean-noël Paoli Thibault Maillot Christelle Gee

subject

[SDV] Life Sciences [q-bio][SDE] Environmental Sciences [SDV]Life Sciences [q-bio][SDE]Environmental Sciences [SDV.BV]Life Sciences [q-bio]/Vegetal Biology traitement d’images [SDV.BV] Life Sciences [q-bio]/Vegetal Biology discrimination culture/adventices information spatiale et spectrale algorithme non supervisé

description

Dans un cadre de diminution des produits phytosanitaires, l'agriculture de précision est une solution technique pour diminuer l'impact environnemental de l'agriculture sans transformer les systèmes de production actuels. La démocratisation des drones aériens pour l'agriculture permet leur utilisation afin de discriminer culture et adventices au sein de parcelles cultivées. Nous avons développé et testé des algorithmes non supervisés (ne nécessitant pas l’intervention d’un humain) combinant l'information spatiale et spectrale pour réaliser cette discrimination. Cette présentation sera l'occasion de revenir sur les résultats de ces algorithmes et de présenter également les limites rencontrées ainsi que des perspectives d'évolution

year	journal	country	edition	language
2019-01-31

https://hal.inrae.fr/hal-02738238

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