Match tier
Likely match
Presence
Current · Arkansas
Last published
2022
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
B
Brayden W. Burns
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Unknown Researcher
2 h-index
2 pubs
120 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: 120
Selected Publications
-
Detecting Intra-Field Variation in Rice Yield With Unmanned Aerial Vehicle Imagery and Deep Learning (2022)
-
Determining nitrogen deficiencies for maize using various remote sensing indices (2022)
Collaboration Network
Top Collaborators
V. Steven Green
Arkansas State University
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
Arkansas State University
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
Agricultural Research Service (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
Fared Farag
Arkansas State University
Remote Sensing in Agriculture
Advanced Neural Network Applications
Plant Physiology and Cultivation Studies
Marc Gomez Prats
University of Arkansas at Fayetteville
Remote Sensing in Agriculture
Rice Cultivation and Yield Improvement
Plant Physiology and Cultivation Studies
Dakota S. Dale
University of Arkansas at Fayetteville
Remote Sensing in Agriculture
Advanced Neural Network Applications
Rice Cultivation and Yield Improvement
Ahmed A. Hashem
Arkansas State University
Remote Sensing in Agriculture
Rice Cultivation and Yield Improvement
Plant Physiology and Cultivation Studies
Cengiz Koparan
University of Arkansas at Fayetteville
Remote Sensing in Agriculture
Advanced Neural Network Applications
Plant Physiology and Cultivation Studies
Donghoon Kim
Arkansas State University
Remote Sensing in Agriculture
Advanced Neural Network Applications
Rice Cultivation and Yield Improvement