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dc.contributor.authorGené Mola, Jordi
dc.contributor.authorGregorio López, Eduard
dc.contributor.authorAuat Cheein, Fernando
dc.contributor.authorGuevara, Javier
dc.contributor.authorLlorens Calveras, Jordi
dc.contributor.authorSanz Cortiella, Ricardo
dc.contributor.authorEscolà i Agustí, Alexandre
dc.contributor.authorRosell Polo, Joan Ramon
dc.coverage.spatialFuji apple orchard, Agramunt, Catalonia, Spainca_ES
dc.descriptionDades primàries associades a un article publicat a la revista Computers and Electronics in Agriculture disponible a l'adreça i a la revista Data in Brief disponible a l'adreça
dc.description.abstractThe LFuji-air dataset contains LiDAR based point clouds of 11 Fuji apples trees and the corresponding apples location ground truth. A mobile terrestrial laser scanner (MTLS) comprised of a LiDAR sensor and a real-time kinematics global navigation satellite system was used to acquire the data. The MTLS was mounted on an air-assisted sprayer used to generate different air flow conditions. A total of 8 scans per tree were performed, including scans from different LiDAR sensor positions (multi-view approach) and under different air flow conditions. These variability of the scanning conditions allows to use the LFuji-air dataset not only for training and testing new fruit detection algorithms, but also to study the usefullness of the multi-view approach and the application of forced air flow to reduce the number of fruit oclusions.ca_ES
dc.description.sponsorshipThis work was partly funded by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya (grant 2017 SGR 646), the Spanish Ministry of Economy and Competitiveness (project AGL2013-48297-C2-2-R) and the Spanish Ministry of Science, Innovation and Universities (project RTI2018-094222-B-I00). The Spanish Ministry of Education is thanked for Mr. J. Gené’s pre-doctoral fellowships (FPU15/03355). The work of Jordi Llorens was supported by the Spanish Ministry of Economy, Industry and Competitiveness through a postdoctoral position named Juan de la Cierva Incorporación (JDCI-2016-29464_N18003). We would also like to thank CONICYT FONDECYT 1171431 and CONICYT FB0008.
dc.publisherUniversitat de Lleidaca_ES
dc.rightscc-by-nc-sa (c) Jordi Gené et al., 2020ca_ES
dc.subjectFruit detectionca_ES
dc.subjectYield predictionca_ES
dc.subjectFruit reflectanceca_ES
dc.subjectComputer visionca_ES
dc.titleLFuji-air dataset [Research data] ca_ES

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cc-by-nc-sa (c) Jordi Gené et al., 2020
Except where otherwise noted, this item's license is described as cc-by-nc-sa (c) Jordi Gené et al., 2020