Steve Hague
Papers
1
Total Citations
3
H-Index
1
About
Steve Hague is a researcher whose work centers on the intersection of agricultural science and computer vision, with a particular focus on cotton phenotyping and precision agriculture. His major contributions lie in pioneering the use of under-canopy imagery—a relatively underexplored method in agricultural research—to capture critical plant data that above-canopy techniques often miss, such as fruiting behavior, early nutrient deficiencies, and disease detection. His most cited paper, "Using under-canopy cotton imagery for cotton variety classification" (2022, 3 citations), demonstrates this novel approach, offering a more granular view of plant health and variety traits. While his citation count is still growing, Hague’s work is notable for challenging conventional remote sensing methods and opening new avenues for in-field monitoring. His research has practical implications for improving crop management and breeding programs, making him a rising voice in the field of agricultural technology. For students and researchers, Hague’s focus on under-canopy imaging highlights the value of thinking beyond standard perspectives to solve real-world agricultural challenges.
Research Focus
Key Achievements
Top Papers
- 1Using under-canopy cotton imagery for cotton variety classification3 citations · 2022