2026-04-13T01:29:53Zhttps://recercat.cat/oai/request

oai:recercat.cat:10459.1/840292024-12-05T22:27:22Zcom_2072_3622col_2072_479130

2024-12-05T22:27:22Z urn:hdl:10459.1/84029 Fruit detection and 3D location using instance segmentation neural networks and SfM photogrammetry Gregorio López, Eduard Sanz Cortiella, Ricardo Rosell Polo, Joan Ramon Morros Rubió, Josep Ramon Ruiz Hidalgo, Javier Vilaplana Besler, Verónica Gregorio López, Eduard Structure-from-motion Fruit detection Fruit location Mask R-CNN Terrestrial remote sensing The development of remote fruit detection systems able to identify and 3D locate fruits provides opportunities to improve the effi-ciency of agriculture management. Most of the current fruit detec-tion systems are based on 2D image analysis. Although the use of 3D sensors is emerging, precise 3D fruit location is still a pending issue. This work presents a new methodology for fruit detection and 3D location, combining the use of instance segmentation neu-ral networks and Structure-from-Motion (SfM) photogrammetry. This work was partly funded by the Secretaria d’Universitats i Recerca de la Gener-alitat de Catalunya (grant 2017 SGR 646), the Spanish Ministry of Economy and Competitiveness (projects AGL2013-48297-C2-2-R and TEC2016-75976-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). 2024-12-05T22:27:22Z 2024-12-05T22:27:22Z 2022-10-31T08:43:23Z 2022-10-31T08:43:23Z 2020 info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion http://hdl.handle.net/10459.1/84029 info:eu-repo/grantAgreement/MINECO//AGL2013-48297-C2-2-R/ES/HERRAMIENTAS DE BASE FOTONICA PARA LA GESTION AGRONOMICA Y EL USO DE PRODUCTOS FITOSANITARIOS SOSTENIBLE EN CULTIVOS ARBOREOS EN EL MARCO DE LA AGRICULTURA DE PRECISION/ info:eu-repo/grantAgreement/MINECO//TEC2016-75976-R/ES/ info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094222-B-I00/ES/TECNOLOGIAS DE AGRICULTURA DE PRECISION PARA OPTIMIZAR EL MANEJO DEL DOSEL FOLIAR Y LA PROTECCION FITOSANITARIA SOSTENIBLE EN PLANTACIONES FRUTALES/ 7th Annual Catalan Meeting on Computer Vision. September 22, 2020, Universitat Autònoma de Barcelona, (http://acmcv.cat/) http://hdl.handle.net/10459.1/67802 (c) J. Gené-Mola et al., 2020 info:eu-repo/semantics/openAccess