QUT-HIA-DAF Capsicum Datasets
Viewed:
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Datasets containing imagery of capsicums, captured under direct sunlight in a field condition and polytunnel environments. Intended for use training machine learning algorihtms for detection, classification and counting of fruit.
Data is made available with the paper:
Michael Halstead, Simon Denman, Clinton Fookes, Chris McCool, "Fruit Detection in the Wild: The Impact of Varying Conditions and Cultivar", DICTA, 2020.
Access rights
The owners of the dataset request that users of the dataset cite the following paper:
Michael Halstead, Simon Denman, Clinton Fookes, Chris McCool, "Fruit Detection in the Wild: The Impact of Varying Conditions and Cultivar", DICTA, 2020.
Geographical area of data collection
kmlPolyCoords
153.649789,-9.210063 137.995957,-9.210063 137.995957,-29.177898 153.649789,-29.177898 153.649789,-9.210063
Publications
Fruit Detection in the Wild: The Impact of Varying Conditions and Cultivar by Michael Halstead, Simon Denman, Clinton Fookes and Chris McCool
http://www.dicta2020.org/wp-content/uploads/2020/09/21_CameraReady.pdf
Research areas
Machine Learning
Computer Vision
Agricultural Robots
Cite this collection
Halstead, Michael; Denman, Simon; Fookes, Clinton; McCool, Chris (2020): QUT-HIA-DAF Capsicum Datasets. Queensland University of Technology. (Dataset) https://doi.org/10.25912/RDF_1610071192071
Partner institution
Hort Innovation
https://www.horticulture.com.au/
Deutsche Forschungsgemeinschaft
https://www.dfg.de/en/
Data file types
All images and accompanying annotations are stored as .tar files.
Licence
Copyright
© Queensland University of Technology, 2020.
Dates of data collection
From 2017-01-01 to 2018-12-31
Contacts
Other
Date record created:
2020-09-15T17:39:26
Date record modified:
2021-01-08T11:59:59
Record status:
Published - Open Access