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KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data

Author
Gené, J.; Vilaplana, V.; Rosell, J.R.; Morros, J.R.; Ruiz-Hidalgo, J.; Gregorio, E.
Type of activity
Journal article
Journal
Data in brief
Date of publication
2019-07-19
Volume
25
First page
104289-1
Last page
104289-5
DOI
10.1016/j.dib.2019.104289
Repository
http://hdl.handle.net/2117/167872 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S2352340919306432?via%3Dihub Open in new window
Abstract
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 barr...
Citation
Gené, J. [et al.]. KFuji RGB-DS database: Fuji apple multi-modal images for fruit detection with color, depth and range-corrected IR data. "Data in brief", 19 Juliol 2019, vol. 25, p. 104289-1-104289-5.
Group of research
GPI - Image and Video Processing Group
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center

Participants

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