Computer Engineering Commons^™

Multispecies Fruit Flower Detection Using A Refined Semantic Segmentation Network, Philipe A. Dias, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existing automated computer vision systems for flower identification are based on hand-engineered techniques that work only under specific conditions and with limited performance. This letter proposes an automated technique for flower identification that is robust to uncontrolled environments and applicable to different flower species. Our method relies on an end-to-end residual convolutional neural network (CNN) that represents the state-of-the-art in semantic segmentation. To enhance …