A/Pr Cheryl McCarthy
Name | A/Pr Cheryl McCarthy |
---|---|
Email Address | cheryl.mccarthy@unisq.edu.au |
Job Title | Associate Professor (Mechatronic Engineering) |
Qualifications | BEng USQ, PhD USQ |
Department | Centre for Agricultural Engineering (Operations) |
Centre for Agricultural Engineering (Research) | |
ORCID | https://orcid.org/0000-0003-3297-7425 |
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Biography
Dr Cheryl McCarthy is a Senior Research Fellow in Mechatronic Engineering and has been a full-time researcher since completing her PhD in 2009. Cheryl's research focuses on automation and machine vision in agriculture for the purpose of developing new technologies for use on-farm.
Employment
Position | Organisation | From | To |
---|---|---|---|
Senior Research Fellow | University of Southern Queensland | 2019 | 2023 |
Research Fellow | University of Southern Queensland | 2011 | 2018 |
Expertise
machine vision, robotics, image analysis, software, sensing
Fields of Research
- 300299. Agriculture, land and farm management not elsewhere classified
- 400899. Electrical engineering not elsewhere classified
BEng
USQ
2005
PhD
USQ
2004
Current Supervisions
Research Title | Supervisor Type | Level of Study | Commenced |
---|---|---|---|
Pre-visual common root rot disease detection in wheat using NIR spectroscopy and UAV-based multispectral imagery | Principal Supervisor | Doctoral | 2021 |
Completed Supervisions
Research Title | Supervisor Type | Level of Study | Completed |
---|---|---|---|
Precision Agriculture: Exploration of machine learning approaches for assessing mango crop quality | Associate | Doctoral | 2020 |
Orchard mapping and mobile robot localisation using on-board camera and laser scanner data fusion | Associate | Doctoral | 2016 |
Precision weed detection via colour and depth fusion in real-time for automatic spot spraying | Principal | Doctoral | 2016 |
Discrimination of wheat crown rot utilising wavelet based models in the NIR spectrum | Principal Supervisor | Doctoral | 2020 |
Automatic plant features recognition using stereo vision for crop monitoring | Associate Supervisor | Doctoral | 2018 |
Machine vision tracking of water advance in cotton surface irrigation with an unmanned aerial system | Principal Supervisor | Doctoral | 2018 |
Project title | Details | Year |
---|---|---|
Farm trials for machine vision of chicken welfare | https://agrifutures.com.au/related-projects/farm-trials-for-machine-vision-of-chicken-welfare/ | 2023 |
Hen health status by machine vision on free range farms | https://www.australianeggs.org.au/what-we-do/leading-research/monitoring-hen-health-with-machine-vision | 2021 |
Feasibility of induction automation R&D | https://www.mla.com.au/research-and-development/reports/2019/feasibility-of-induction-automation-rd---phase-1/ | 2019 |
Harvester losses assessment by real-time machine vision systems | https://www.growag.com/listings/research-project/harvester-losses-assessment-by-real-time-machine-vision-systems-1 | 2019 |
Precision management for improved cotton quality | https://www.growag.com/listings/research-project/precision-management-for-improved-cotton-quality | 2017 |
Novel detection of chicken welfare using machine vision | https://agrifutures.com.au/related-projects/novel-detection-of-chicken-welfare-using-machine-vision/ | 2017 |
Field ready, optimised precision weed identification sensor system | https://elibrary.sugarresearch.com.au/handle/11079/18032 | 2016 |
Item reviewed | Year |
---|---|
Advances in Agri-Food Robotics | 2024 |