Mapping almond orchard canopy volume, flowers, fruit and yield using lidar and vision sensors. - James Patrick Underwood; Calvin Hung; Brett Whelan; Salah Sukkarieh (Comput. Electron. Agric., 2016)

Temperature-dependent hysteresis effects on EM induction instruments: An example of single-frequency multi-coil array instruments. - Jingyi Huang; Budiman Minasny; Brett Whelan; Alex B. McBratney; John Triantafilis (Comput. Electron. Agric., 2017)

Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review. - Anna Chlingaryan; Salah Sukkarieh; Brett Whelan (Comput. Electron. Agric., 2018)

Segmentation of lettuce in coloured 3D point clouds for fresh weight estimation. - Anders Krogh Mortensen; Asher Bender; Brett Whelan; Margaret M. Barbour; Salah Sukkarieh; Henrik Karstoft; René Gislum (Comput. Electron. Agric., 2018)

A high-resolution, multimodal data set for agricultural robotics: A Ladybird's-eye view of Brassica. - Asher Bender; Brett Whelan; Salah Sukkarieh (J. Field Robotics, 2020)

Mapping of Cotton Fields Within-Season Using Phenology-Based Metrics Derived from a Time Series of Landsat Imagery. - Dhahi Alshammari; Ignacio Fuentes; Brett Whelan; Patrick Filippi; Thomas F. A. Bishop (Remote. Sens., 2020)

Ten years of corn yield dynamics at field scale under digital agriculture solutions: A case study from North Italy. - Ahmed Kayad; Marco Sozzi; Simone Gatto; Brett Whelan; Luigi Sartori; Francesco Marinello (Comput. Electron. Agric., 2021)

Machine Learning Optimised Hyperspectral Remote Sensing Retrieves Cotton Nitrogen Status. - Ian J. Marang; Patrick Filippi; Tim B. Weaver; Bradley J. Evans; Brett Whelan; Thomas F. A. Bishop; Mohammed O. F. Murad; Dhahi Alshammari; Guy Roth (Remote. Sens., 2021)

Identifying causes of crop yield variability with interpretive machine learning. - Edward J. Jones; Thomas F. A. Bishop; Brendan P. Malone; Patrick J. Hulme; Brett Whelan; Patrick Filippi (Comput. Electron. Agric., 2022)