01165nam a2200301 a 450000100080000000500110000800800410001902200140006002400520007410000230012624500920014926001570024150000180039852001710041665000200058765000190060765000120062665000120063865300350065065300420068565300250072770000150075270000210076770000180078870000190080670000210082570000170084621608272024-01-16       2023    bl uuuu     u00u1 u    #d  a2177-97247 ahttps://doi.org/10.5753/sbiagro.2023.265672DOI1 aSOUZA, K. X. S. de  aEvaluating multiple regressors for the yield of orange orchards.h[electronic resource]  aIn: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 14., 2023, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023. p. 262-269.c2023  aSBIAgro 2023.  aIn this paper, we assess the effectiveness of various machine learning regressors for yield forecasting based on fruit detection in images captured within the orchard  aComputer vision  aImage analysis  aOranges  aLaranja  aAutomatic fruit identification  aIdentificação automática de frutas  aVisão computacional1 aTERNES, S.1 aCAMARGO NETO, J.1 aSANTOS, T. T.1 aMOREIRA, A. S.1 aKOENIGKAN, L. V.1 aSOUZA, R. de