| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4970354 | Pattern Recognition Letters | 2016 | 14 Pages |
Abstract
In this paper we present a collection of benchmark datasets for the development and evaluation of computer vision and machine learning algorithms in the context of plant phenotyping. We provide annotated imaging data and suggest suitable evaluation criteria for plant/leaf segmentation, detection, tracking as well as classification and regression problems. The Figure symbolically depicts the data available together with ground truth segmentations and further annotations and metadata.432
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Massimo Minervini, Andreas Fischbach, Hanno Scharr, Sotirios A. Tsaftaris,