Instance segmentation for the fine detection of crop and weed plants by precision agricultural robots

• Published in: Applications in plant sciences Vol. 8; no. 7; pp. e11373 - n/a
• Main Authors: Champ, Julien, Mora‐Fallas, Adan, Goëau, Hervé, Mata‐Montero, Erick, Bonnet, Pierre, Joly, Alexis
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.07.2020; Wiley; John Wiley and Sons Inc
• Subjects: Agricultural production; Agriculture; Algorithms; Application; autonomous robot; Biodiversity; Biodiversity and Ecology; Botanics; convolutional neural network; Corn; Crops; data collection; Deep learning; digital agriculture; Ecology, environment; Ecosystems; electric potential difference; electrodes; Environmental Sciences; Herbicides; Life Sciences; Neural networks; plant detection; Plant sciences; risk; Robots; Segmentation; Semantics; Species; Systematics, Phylogenetics and taxonomy; Vegetal Biology; weed electrification; Weeds; France; United States > US; plant detection; weed electrification; deep learning; digital agriculture; autonomous robot; convolutional neural network; Deep learning; Autonomous robot; Plant detection; Weed electrification; Convolutional neural network; Digital agriculture

Premise Weed removal in agriculture is typically achieved using herbicides. The use of autonomous robots to reduce weeds is a promising alternative solution, although their implementation requires the precise detection and identification of crops and weeds to allow an efficient action. Methods We tr...