Paper record
Machine learning for high-throughput field phenotyping and image processing provides insight into the association of above and below-ground traits in cassava (Manihot esculenta Crantz)
Research Square · 21 Feb 2020 · 10.21203/rs.2.24148/v1
Abstract
Abstract has not been obtained from indexed metadata or an accessible article page.
Code and data availability
The paper describes the CIAT Pheno-i web-based image analysis platform developed by the authors and used for this study's phenotyping, which is publicly accessible. However, no public deposit of the paper's phenotype datasets, UAV imagery, ML models, or analysis code is stated; supplementary files (ML model PDF, tables
No evidence-backed public reproduction asset is currently recorded.
Other versions of this study