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| Web URL(s): | https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/152574
Last checked: 12/07/2023 |
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| Publication Type:
| Report |
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| Content Type: | Abstract or Summary only |
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| Author(s): | Maleski, Jerome;
Zhang, Jing;
Vines, Phillip L.;
Schwartz, Brian M. |
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| Author Affiliation: | Maleski: Presenting Author and University of Georgia-Tifton, Tifton, GA; Zhang: Georgia, University of Georgia-Tifton, Tifton, GA; Vines and Schwartz: Department of Crop and Soil Sciences, University of Georgia, Tifton, GA |
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| Title: | Computer vision for turfgrass quality assessment |
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| Section: | Turfgrass science poster
Other records with the "Turfgrass science poster" Section
C05 turfgrass science
Other records with the "C05 turfgrass science" Section
520
Other records with the "520" Section
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| Meeting Info.: | St. Louis, Missouri: October 29-November 1, 2023 |
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| Source: | ASA, CSSA, SSSA International Annual Meeting. 2023, p. 152574. |
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| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America] |
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| # of Pages: | 1 |
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| Abstract/Contents: | "Computer vision is used to rate turf quality and is compared to human ratings. This tool can be combined with drone imaging flights for high throughput turf selection and ratings." |
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| Language: | English |
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| References: | 0 |
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| Note: | This item is an abstract only! |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Maleski, J., J. Zhang, P. L. Vines, and B. M. Schwartz. 2023. Computer vision for turfgrass quality assessment. Agron. Abr. p. 152574. |
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| Web URL(s):
https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/152574
Last checked: 12/07/2023 |
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