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Gené-Mola J, Gregorio E, Guevara J, Auat F, Escolà A, Morros JR, et al.. Fruit Detection Using Mobile Terrestrial Laser Scanning. In AgEng 2018,. Wageningen (Netherlands); 2018.
Gené-Mola J, Felip-Pomés M, Net-Barnés F, Morros JR, Miranda JC, J. Satorra A, et al.. Video-Based Fruit Detection and Tracking for Apple Counting and Mapping. In IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). 2023.  (680.49 KB)
Gené-Mola J, Sanz R, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Vilaplana V, et al.. Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry. Computers and Electronics in Agriculture. 2020;169.
Gené-Mola J, Ferrer-Ferrer M, Hemming J, Dalfsen P, Hoog D, Sanz-Cortiella R, et al.. AmodalAppleSize_RGB-D dataset: RGB-D images of apple trees annotated with modal and amodal segmentation masks for fruit detection, visibility and size estimation. Data in Brief. 2024;52.
Gené-Mola J, Gregorio E, Guevara J, Cheein FAuat, Sanz R, Escolà A, et al.. Fruit Detection in an Apple Orchard Using a Mobile Terrestrial Laser Scanner. Biosystems Engineering. 2019;187.
Gené-Mola J, Vilaplana V, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Gregorio E. Uso de redes neuronales convolucionales para la detección remota de frutos con cámaras RGB-D. In Congreso Ibérico de Agroingeniería. Huesca: Universidad de Zaragoza (UZA); 2019.  (1.21 MB)
Gené-Mola J, Vilaplana V, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Gregorio E. KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data. Data in Brief. 2019;.  (2.43 MB)
Gené-Mola J, Ferrer-Ferrer M, Gregorio E, Blok PM, Hemming J, Morros JR, et al.. Looking behind occlusions: A study on amodal segmentation for robust on-tree apple fruit size estimation. Computers and Electronics in Agriculture. 2023;209.  (9.02 MB)
Gené-Mola J, Vilaplana V, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Gregorio E. Multi-modal Deep Learning for Fuji Apple Detection Using RGB-D Cameras and their Radiometric Capabilities. Computers and Electronics in Agriculture. 2019;162.
Gené-Mola J, Sanz R, Rosell-Polo JR, Morros JR, Ruiz-Hidalgo J, Vilaplana V, et al.. Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry. 2020;Data in Brief(Vol. 30).