C. Blattert

A Deep Learning Model for Tree Species Instance Segmentation and Classification Using Ground-Level RGB Imagery and Automated Annotations

This work introduces a new “in-situ” forest image dataset alongside an automated labeling pipeline that complements existing methods for detecting tree positions and diameters, facilitating the creation of a holistic, cost-effective, and scalable forest inventory dataset.