Brett Whelan

According to our database, Brett Whelan authored at least 9 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

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

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

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

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

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

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

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

2017

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

2016

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