Given the rapid development of plant genomic technologies, a lack of access to plant
phenotyping capabilities limits our ability to dissect the genetics of quantitative traits …

Highlights•State of high-throughput imaging technologies.•Highlights of Maker-type
phenotyping technologies.•Table of well-curated publically available high-throughput …

Highlights•A convolutional neural network is designed to determine the species of
seedlings.•The system is trained and tested on images of 22 plant species.•The images are …

Plant phenomics has received increasing interest in recent years in an attempt to bridge the
genotype-to-phenotype knowledge gap. There is a need for expanded high-throughput …

Deep learning presents many opportunities for image-based plant phenotyping. Here we
consider the capability of deep convolutional neural networks to perform the leaf counting …

Instance segmentation is the problem of detecting and delineating each distinct object of
interest appearing in an image. Current instance segmentation approaches consist of …

Image-based approaches to plant phenotyping are gaining momentum providing fertile
ground for several interesting vision tasks where fine-grained categorization is necessary …

Image-based plant phenotyping is a growing application area of computer vision in
agriculture. A key task is the segmentation of all individual leaves in images. Here we focus …

In this paper, we investigate the problem of counting rosette leaves from an RGB image, an
important task in plant phenotyping. We propose a data-driven approach for this task …

Rhododendron delavayi Franch. is globally famous as an ornamental plant. Its distribution in
southwest China covers several different habitats and environments. However, not much …