Title:	Using brainwave patterns recorded from plant pathology experts to increase the reliability of ai-based plant disease recognition system.
Authors:	MEIR, Y. BARBEDO, J. G. A. KEREN, O. GODOY, C. V. AMEDI, N. SHALOM, Y. GEVA, A. B.
Affiliation:	YONATAN MEIR, INNEREYE LTD.; JAYME GARCIA ARNAL BARBEDO, CNPTIA; OMRI KEREN, INNEREYE LTD.; CLAUDIA VIEIRA GODOY, CNPSO; NOFAR AMEDI, INNEREYE LTD.; YAAR SHALOM, INNEREYE LTD.; AMIR B. GEVA, INNEREYE LTD., BEN GURION UNIVERSITY.
Date Issued:	2023
Citation:	Sensors, v. 23, n. 9, 4272, 2023.
Pages:	13 p.
Description:	This study investigates how the use of electroencephalograms from plant pathology experts can improve the accuracy and robustness of image-based artificial intelligence models dedicated to plant disease recognition.
Thesagro:	Soja
NAL Thesaurus:	Soybeans Digital images Plant pathology Plant diseases and disorders Artificial intelligence
Keywords:	Patologia de planta Ondas cerebrais Eletroencefalograma Imagem digital Aprendizado ativo Inteligência artificial Electroencephalogram Labeling Active learning
DOI:	10.3390/s23094272
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CNPSO)