A fast and accurate deep learning method for strawberry instance segmentation

摘要

Fruit instance segmentation is a key element for autonomous picking systems. This paper proposes a methodology for instance segmentation of strawberries using deep learning techniques. This methodology presents the following changes in relation to the well-known Mask R-CNN network: a new architecture is designed for the backbone and the mask network; the object classifier and the bounding-box regressor are removed; the non-maximum suppression algorithm is replaced with a new region grouping and filtering algorithm without increasing the order of complexity.