KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data
| العنوان: | KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data |
|---|---|
| المؤلفون: | Eduard Gregorio, Josep Ramon Morros, Joan R. Rosell-Polo, Javier Ruiz-Hidalgo, Jordi Gené-Mola, Verónica Vilaplana |
| المساهمون: | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo |
| المصدر: | Recercat. Dipósit de la Recerca de Catalunya instname Repositorio Abierto de la UdL Universitad de Lleida Data in Brief, Vol 25, Iss, Pp-(2019) Data in Brief UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| بيانات النشر: | Elsevier, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Computer science, fruit detection, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Informàtica::Sistemes d'informació::Bases de dades [Àrees temàtiques de la UPC], lcsh:Computer applications to medicine. Medical informatics, computer.software_genre, 03 medical and health sciences, Imatges -- Processament -- Tècniques digitals, 0302 clinical medicine, Agricultural and Biological Science, Color depth, Range (statistics), Fruit detection, Fuji apple, Research article, lcsh:Science (General), 030304 developmental biology, Depth cameras, 0303 health sciences, Ground truth, Image processing--Digital techniques, Multidisciplinary, Database, Apples, Fruit reflectance, business.industry, Multi-modal dataset, RGB-D cameras, Deep learning, Digital video, RGB-D, Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo [Àrees temàtiques de la UPC], Modal, Vídeo digital, Enginyeria agroalimentària::Indústries agroalimentàries::Productes d'origen vegetal [Àrees temàtiques de la UPC], lcsh:R858-859.7, RGB color model, Color data, Artificial intelligence, Pomes, business, computer, 030217 neurology & neurosurgery, lcsh:Q1-390, Aprenentatge profund |
| الوصف: | This article contains data related to the research article entitle 'Multi-modal Deep Learning for Fruit Detection Using RGB-D Cameras and their Radiometric Capabilities' [1]. The development of reliable fruit detection and localization systems is essential for future sustainable agronomic management of high-value crops. RGB-D sensors have shown potential for fruit detection and localization since they provide 3D information with color data. However, the lack of substantial datasets is a barrier for exploiting the use of these sensors. This article presents the KFuji RGBDS database which is composed by 967 multi-modal images of Fuji apples on trees captured using Microsoft Kinect v2 (Microsoft, Redmond, WA, USA). Each image contains information from 3 different modalities: color (RGB), depth (D) and range corrected IR intensity (S). Ground truth fruit locations were manually annotated, labeling a total of 12,839 apples in all the dataset. The current dataset is publicly available at http://www.grap.udl.cat/publicacions/datasets.html. This work was partly funded by the Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya, the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (ERDF) under Grants 2017 SGR 646, AGL2013-48297-C2-2-R and MALEGRA, TEC2016-75976-R. The Spanish Ministry of Education is thanked for Mr. J. Gené’s pre-doctoral fellowships (FPU15/03355). We would also like to thank Nufri and Vicens Maquinària Agrícola S.A. for their support during data acquisition. |
| وصف الملف: | application/pdf |
| اللغة: | English |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eec56a1849752f4945bf8ec78f597c46 https://hdl.handle.net/2117/167872 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....eec56a1849752f4945bf8ec78f597c46 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |