Long, Derek 
ORCID: https://orcid.org/0000-0001-9414-5064
(2018)
Machine vision tracking of water advance in cotton
surface irrigation with an unmanned aerial system.
[Thesis (PhD/Research)]
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| Item Type: | Thesis (PhD/Research) |
|---|---|
| Item Status: | Live Archive |
| Additional Information: | Doctor of Philosophy (PhD) thesis. Access to this thesis permanently restricted at author's request. |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | McCarthy, Cheryl; Jensen, Troy |
| Date Deposited: | 21 Jan 2019 01:44 |
| Last Modified: | 20 Nov 2020 04:19 |
| Uncontrolled Keywords: | cotton surface irrigation, thermal imagery, image analysis |
| Fields of Research (2008): | 07 Agricultural and Veterinary Sciences > 0799 Other Agricultural and Veterinary Sciences > 079901 Agricultural Hydrology (Drainage, Flooding, Irrigation, Quality, etc.) 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing |
| Fields of Research (2020): | 30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300201 Agricultural hydrology 46 INFORMATION AND COMPUTING SCIENCES > 4603 Computer vision and multimedia computation > 460306 Image processing |
| Identification Number or DOI: | doi:10.26192/5f643ba5ce22b |
| URI: | http://eprints.usq.edu.au/id/eprint/35499 |
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