Detection of sunn pest-damaged wheat grains using artificial bee colony optimization-based artificial intelligence techniques.

Source: PubMed
Journal of the science of food and agriculture
Jan 30, 2020;100 (2): 817-824.
Detection of sunn pest-damaged wheat grains using artificial bee colony optimization-based artificial intelligence techniques.
Kadir Sabanci
Author Information
Kadir Sabanci: Department of Electrical Electronics Engineering, Engineering Faculty, Karamanoglu Mehmetbey University, Karaman, Turkey. ORCID
PMID: 31646637
DOI: 10.1002/jsfa.10093
Abstract
BACKGROUND: In this study, artificial intelligence models that identify sunn pest-damaged wheat grains (SDG) and healthy wheat grains (HWG) are presented. S

原文链接：https://ngdc.cncb.ac.cn/openlb/publication/OLB-PM-31646637