B
Brayden W. Burns Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
unknown
2 h-index
2 pubs
113 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Brayden W. Burns is a researcher whose work focuses on the application of remote sensing and deep learning techniques in agriculture. His recent publications investigate the use of Unmanned Aerial Vehicle (UAV) imagery and various remote sensing indices to detect nitrogen deficiencies in maize and to identify intra-field variations in rice yield. Burns has published two papers, accumulating 104 citations, and holds an h-index of 2. He collaborates with researchers at Arkansas State University, including Ahmed A. Hashem and V. Steven Green, and with Benjamin R. K. Runkle from the University of Arkansas at Fayetteville.
Metrics
- h-index: 2
- Publications: 2
- Citations: 113
Selected Publications
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Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning (2022)
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Determining nitrogen deficiencies for maize using various remote sensing indices (2022)
Collaboration Network
Top Collaborators
V. Steven Green
University of Arkansas System
2 shared publications
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Ahmed A. Hashem
University of Arkansas System
2 shared publications
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
J.H. Massey
United States Department of Agriculture (US)
1 shared publication
- Determining nitrogen deficiencies for maize using various remote sensing indices
Aaron M. Shew
Arkansas State University
1 shared publication
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
Maria Arlene Adviento‐Borbe
United States Department of Agriculture (US)
1 shared publication
- Determining nitrogen deficiencies for maize using various remote sensing indices
Mohamed Milad
Arkansas State University
1 shared publication
In database
- Determining nitrogen deficiencies for maize using various remote sensing indices
Emily S. Bellis
Arkansas State University
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Jason Causey
Arkansas State University
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Benjamin R. K. Runkle
United States Department of Agriculture
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Beatriz Moreno‐García
United States Department of Agriculture
1 shared publication
In database
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Timothy N. Burcham
University of Arkansas System (US)
1 shared publication
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Michele L. Reba
Delta Water Management Research Unit (US)
1 shared publication
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Xiuzhen Huang
Arkansas State University (US)
1 shared publication
- Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning
Similar Researchers
Based on overlapping research topics
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Arkansas State University
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