no code implementations • 7 Feb 2021 • Fredrik Westling, James Underwood, Mitch Bryson
We present a framework for suggesting pruning strategies on LiDAR-scanned commercial fruit trees using a scoring function with a focus on improving light distribution throughout the canopy.
1 code implementation • 24 Nov 2020 • Fredrik Westling, Mitch Bryson, James Underwood
We present an open source tool, SimTreeLS (Simulated Tree Laser Scans), for generating point clouds which simulate scanning with user-defined sensor, trajectory, tree shape and layout parameters.
no code implementations • 4 Nov 2018 • Xu Liu, Steven W. Chen, Chenhao Liu, Shreyas S. Shivakumar, Jnaneshwar Das, Camillo J. Taylor, James Underwood, Vijay Kumar
We present a cheap, lightweight, and fast fruit counting pipeline that uses a single monocular camera.
Robotics
no code implementations • 4 Sep 2017 • Alexander Wendel, James Underwood
This paper focuses on the common case where a mobile platform is equipped with a rigidly mounted line scanning camera, whose pose is unknown, and a navigation system providing vehicle body pose estimates.
no code implementations • 9 Jun 2017 • Mikkel Kragh, James Underwood
Results showed that for a two-class classification problem (ground and nonground), only the camera leveraged from information provided by the other modality with an increase in the mean classification score of 0. 5%.
no code implementations • 25 Oct 2016 • Suchet Bargoti, James Underwood
This paper presents an image processing framework for fruit detection and counting using orchard image data.
no code implementations • 12 Oct 2016 • Suchet Bargoti, James Underwood
This paper presents the use of a state-of-the-art object detection framework, Faster R-CNN, in the context of fruit detection in orchards, including mangoes, almonds and apples.