An End-to-End Deep RNN based Network Structure to Precisely Regress the
Height of Lettuce by Single Perspective Sparse Point Cloud
Abstract
Focusing on non-destructive and automated acquisition of plant
phenotypic parameters,this extended abstract proposed an end-to-end deep
RNN based network structure for single perspective sparse raw point
cloud regression task called DRN. It has been proven to achieve accuracy
improvements in PointNet++ and PonitCNN when it comes to regression of
lettuce plant height. We believe DRN structure is suitable for feature
extraction from plant point cloud data and regression of spatial
distance related plant phenotypes like plant height.