Deep Learning in Plant Phenological Research: A Systematic Literature Review.

ABSTRACT: Climate change represents one of the most critical threats to biodiversity with far-reaching consequences for species interactions, the functioning of ecosystems, or the assembly of biotic communities. Plant phenology research has gained increasing attention as the timing of periodic events in plants is strongly affected by seasonal and interannual climate variation. Recent technological development allowed us to gather invaluable data at a variety of spatial and ecological scales. The feasibility of phenological monitoring today and in the future depends heavily on developing tools capable of efficiently analyzing these enormous amounts of data. Deep Neural Networks learn representations from data with impressive accuracy and lead to significant breakthroughs in, e.g., image processing. T

SUBMITTER: Katal N 

PROVIDER: S-EPMC8969581 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature