Multi-modal deep learning for Fuji apple detection using RGB-D cameras and their radiometric capabilities-Reference-Cited by-同舟云学术

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Multi-modal deep learning for Fuji apple detection using RGB-D cameras and their radiometric capabilities

Published:2019-07 Issue: Volume:162 Page:689-698
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Gené-Mola Jordi,Vilaplana Verónica,Rosell-Polo Joan R.,Morros Josep-Ramon,Ruiz-Hidalgo Javier,Gregorio Eduard

Funder

Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya

Spanish Ministry of Economy and Competitiveness

European Regional Development Fund

Spanish Ministry of Education

Publisher

Elsevier BV

Subject

Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry

Reference47 articles.

1. A deep learning-based approach for banana leaf diseases classification;Amara,2017

2. Agricultural robotics: unmanned robotic service units in agricultural tasks;Auat Cheein;IEEE Ind. Electron. Mag.,2013

3. Bargoti, S., 2016. Pychet Labeller. Available online: .

4. Deep fruit detection in orchards;Bargoti,2017

5. Image segmentation for fruit detection and yield estimation in apple orchards;Bargoti;J. F. Robot.,2017

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