Deploying Deep Neural Networks on Edge Devices for Grape Segmentation
| Autor: | Nathalie Gaveau, François Alin, Luiz Angelo Steffenel, Mathias Roesler, Lucas Mohimont |
|---|---|
| Přispěvatelé: | Laboratoire d'Informatique en Calcul Intensif et Image pour la Simulation (LICIIS), Université de Reims Champagne-Ardenne (URCA), Résistance Induite et Bioprotection des Plantes - EA 4707 (RIBP), Université de Reims Champagne-Ardenne (URCA)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), European Project: 826060,AI4DI, Université de Reims Champagne-Ardenne (URCA)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Artificial neural network
Edge device Computer science business.industry Deep learning 010401 analytical chemistry 020206 networking & telecommunications Pattern recognition 02 engineering and technology 01 natural sciences Object detection 0104 chemical sciences Precision viticulture 0202 electrical engineering electronic engineering information engineering Segmentation Artificial intelligence Enhanced Data Rates for GSM Evolution [INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC] business Edge computing ComputingMilieux_MISCELLANEOUS |
| Zdroj: | International Conference on Smart and Sustainable Agriculture (SSA'2021) International Conference on Smart and Sustainable Agriculture (SSA'2021), Jun 2021, virtual, France. pp.30-43, ⟨10.1007/978-3-030-88259-4_3⟩ International Conference on Smart and Sustainable Agriculture Communications in Computer and Information Science Communications in Computer and Information Science-Smart and Sustainable Agriculture Smart and Sustainable Agriculture ISBN: 9783030882587 |
| ISSN: | 1865-0929 1865-0937 |
| DOI: | 10.1007/978-3-030-88259-4_3⟩ |
| Popis: | Deep learning (DL) is a hot trend for object detection and segmentation, thanks to the use of Deep Neural Networks (DNNs). Image recognition is a powerful tool for precision viticulture, having a strong potential in cases such as yield estimation and automatic quality estimation of the grapes. Developing the models is one part of the problem, deploying them in the field, at the edge of the network, is another problem that comes with its own constraints. This paper studies the use of embedded devices to run Deep Neural Network algorithms for real-time grape segmentation at the wine press. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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