Title:	Evaluating multiple regressors for the yield of orange orchards.
Authors:	SOUZA, K. X. S. de TERNES, S. CAMARGO NETO, J. SANTOS, T. T. MOREIRA, A. S. KOENIGKAN, L. V. SOUZA, R. de
Affiliation:	KLEBER XAVIER SAMPAIO DE SOUZA, CNPTIA; SONIA TERNES, CNPTIA; JOAO CAMARGO NETO, CNPTIA; THIAGO TEIXEIRA SANTOS, CNPTIA; ALECIO SOUZA MOREIRA, CNPMF; LUCIANO VIEIRA KOENIGKAN, CNPTIA; ROBERTA DE SOUZA.
Date Issued:	2023
Citation:	In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 14., 2023, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023. p. 262-269.
Description:	In this paper, we assess the effectiveness of various machine learning regressors for yield forecasting based on fruit detection in images captured within the orchard
Thesagro:	Laranja
NAL Thesaurus:	Oranges Computer vision Image analysis
Keywords:	Visão computacional Identificação automática de frutas Automatic fruit identification
ISSN:	2177-9724
DOI:	https://doi.org/10.5753/sbiagro.2023.26567
Notes:	SBIAgro 2023.
Type of Material:	Artigo em anais e proceedings
Access:	openAccess
Appears in Collections:	Artigo em anais de congresso (CNPTIA)