A Public Image Database for Benchmark of Plant Seedling Classification Algorithms
This provides a resource for researchers in agricultural AI and computer vision to benchmark classification algorithms, but it is incremental as it focuses on data availability rather than new methods.
The authors tackled the lack of standardized data for plant seedling classification by creating a public database of 960 plants across 12 species with annotated RGB images, and they proposed an F1 score benchmark for evaluation.
A database of images of approximately 960 unique plants belonging to 12 species at several growth stages is made publicly available. It comprises annotated RGB images with a physical resolution of roughly 10 pixels per mm. To standardise the evaluation of classification results obtained with the database, a benchmark based on $f_{1}$ scores is proposed. The dataset is available at https://vision.eng.au.dk/plant-seedlings-dataset