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 > Comparing deep-learning networks for apple fruit detection to classical hard-coded algorithms

Articles

Comparing deep-learning networks for apple fruit detection to classical hard-coded algorithms

Article number

1279_31

Pages

209 – 216

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

K. Bresilla, G.D. Perulli, A. Boini, B. Morandi, L.C. Grappadelli, L. Manfrini

Keywords

computer vision, convolution neural networks, fruit recognition, precision fruit growing

Full text

https://doi.org/10.17660/ActaHortic.2020.1279.31

Groups involved

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