Evaluating multiple regressors for the yield of orange orchards.

Evaluating multiple regressors for the yield of orange orchards.

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

Saved in:
Bibliographic Details
Main Authors: SOUZA, K. X. S. de, TERNES, S., CAMARGO NETO, J., SANTOS, T. T., MOREIRA, A. S., KOENIGKAN, L. V., SOUZA, R. de
Other Authors: 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.
Format: Artigo em anais e proceedings biblioteca
Language:Ingles
English
Published: 2024-01-15
Subjects:Visão computacional, Identificação automática de frutas, Automatic fruit identification, Laranja, Oranges, Computer vision, Image analysis,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1160827
https://doi.org/10.5753/sbiagro.2023.26567
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.alice.cnptia.embrapa.br/alice/handle/doc/1160827
https://doi.org/10.5753/sbiagro.2023.26567

Similar Items