Pheno-Deep Counter: a unified and versatile deep learning architecture for leaf counting.

ABSTRACT: Direct observation of morphological plant traits is tedious and a bottleneck for high-throughput phenotyping. Hence, interest in image-based analysis is increasing, with the requirement for software that can reliably extract plant traits, such as leaf count, preferably across a variety of species and growth conditions. However, current leaf counting methods do not work across species or conditions and therefore may lack broad utility. In this paper, we present Pheno-Deep Counter, a single deep network that can predict leaf count in two-dimensional (2D) plant images of different species with a rosette-shaped appearance. We demonstrate that our architecture can count leaves from multi-modal 2D images, such as visible light, fluorescence and near-infrared. Our network design is flexible, allo

SUBMITTER: Giuffrida MV 

PROVIDER: S-EPMC6282617 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature