Next Article in Journal
Monitoring Plant Functional Diversity Using the Reflectance and Echo from Space
Previous Article in Journal
Estimation of Forest Growing Stock Volume with UAV Laser Scanning Data: Can It Be Done without Field Data?
Open AccessTechnical Note

Open Plant Phenotype Database of Common Weeds in Denmark

1
Department of Engineering, Aarhus University, DK-8200 Aarhus N, Denmark
2
Department of Agroecology, Aarhus University, DK-4200 Slagelse, Denmark
3
School of Engineering, Aarhus University, DK-8200 Aarhus N, Denmark
4
I·GIS A/S, DK-8240 Risskov, Denmark
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(8), 1246; https://doi.org/10.3390/rs12081246
Received: 12 February 2020 / Revised: 8 April 2020 / Accepted: 9 April 2020 / Published: 15 April 2020
(This article belongs to the Section Remote Sensing in Agriculture and Vegetation)
For decades, significant effort has been put into the development of plant detection and classification algorithms. However, it has been difficult to compare the performance of the different algorithms, due to the lack of a common testbed, such as a public available annotated reference dataset. In this paper, we present the Open Plant Phenotype Database (OPPD), a public dataset for plant detection and plant classification. The dataset contains 7590 RGB images of 47 plant species. Each species is cultivated under three different growth conditions, to provide a high degree of diversity in terms of visual appearance. The images are collected at the semifield area at Aarhus University, Research Centre Flakkebjerg, Denmark, using a customized data acquisition platform that provides well-illuminated images with a ground resolution of ∼6.6 px mm 1 . All images are annotated with plant species using the EPPO encoding system, bounding box annotations for detection and extraction of individual plants, applied growth conditions and time passed since seeding. Additionally, the individual plants have been tracked temporally and given unique IDs. The dataset is accompanied by two experiments for: (1) plant instance detection and (2) plant species classification. The experiments introduce evaluation metrics and methods for the two tasks and provide baselines for future work on the data. View Full-Text
Keywords: dataset; plant phenotyping; plant seedlings; weed control dataset; plant phenotyping; plant seedlings; weed control
Show Figures

Graphical abstract

MDPI and ACS Style

Leminen Madsen, S.; Mathiassen, S.K.; Dyrmann, M.; Laursen, M.S.; Paz, L.-C.; Jørgensen, R.N. Open Plant Phenotype Database of Common Weeds in Denmark. Remote Sens. 2020, 12, 1246.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop