Published December 4, 2021
| Version v1
Conference paper
Early detection of damages in fruits with amplitude-only measurements
Contributors
Others:
- Laboratoire d'Electronique, Antennes et Télécommunications (LEAT) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- Institut FRESNEL (FRESNEL) ; Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)
- IEEE
Description
Fighting fruit diseases, farmers are in demand of an automatic Non Destructive Evaluation system for detecting the damages in fruits. In this paper, we propose a proof of concept using amplitude-only measurements associated with a Machine learning Algorithm of linear Support Vector Machine type, for sorting healthy from damaged peaches hidden by leaves. The system operates in W-band and the total accuracy of the classifier is 100%
Abstract
International audienceAdditional details
Identifiers
- URL
- https://hal.archives-ouvertes.fr/hal-03525894
- URN
- urn:oai:HAL:hal-03525894v1
Origin repository
- Origin repository
- UNICA