Home > XXX International Horticultural Congress IHC2018: VII Conference on Landscape and Urban Horticulture, IV Conference on Turfgrass Management and Science for Sports Fields and II Symposium on Mechanization, Precision Horticulture, and Robotics > Is machine learning efficient for mango yield estimation when used under heterogeneous field conditions?

Articles

Is machine learning efficient for mango yield estimation when used under heterogeneous field conditions?

Article number

1279_30

Pages

201 – 208

Language

English

Abstract

Publication

XXX International Horticultural Congress IHC2018: VII Conference on Landscape and Urban Horticulture, IV Conference on Turfgrass Management and Science for Sports Fields and II Symposium on Mechanization, Precision Horticulture, and Robotics

Authors

J. Sarron, C.A.B. Sané, P. Borianne, E. Malézieux, T. Nordey, F. Normand, P. Diatta, Y. Niang, E. Faye

Keywords

image analysis, automated fruit counting, k-nearest neighbours, algorithm efficiency, Senegal

Full text

https://doi.org/10.17660/ActaHortic.2020.1279.30

Groups involved

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