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Aliloo, J
Bari, M.A
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Authors
Aliloo, J
Abbasi, E
Karamidehkordi , E
Ghanbari Parmehr, E
Canavari, M
Vitali, G.-
Bari, M.A
Bakshi, A
Witt, T
Caragea, D
Jagadish, K
Felderhoff, T
Pramanik, S
Choton, J
Topics
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2024
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1. Content Analysis of the Challenges of Using Drones in Paddy Fields in the Haraz Plain Watershed, Iran

Drone technology has gained popularity in recent years as a sustainable solution to changing agricultural conditions. Using drones in agriculture provides many advantages in farm management. However, the use of drones in paddy fields in Iran is a new phenomenon facing numerous challenges. This study aims to explore the challenges for using drones in paddy fields and provide practical guidelines to solve the challenges facing the their application. This research was conducted with a qualitative... J. Aliloo, E. Abbasi, E. Karamidehkordi , E. Ghanbari parmehr, M. Canavari, G.-. Vitali

2. Deep Learning to Estimate Sorghum Yield with Uncrewed Aerial System Imagery

In the face of growing demand for food, feed, and fuel, plant breeders are challenged to accelerate yield potential through quick and efficient cultivar development. Plant breeders often conduct large-scale trials in multiple locations and years to address these goals. Sorghum breeding, integral to these efforts, requires early, accurate, and scalable harvestable yield predictions, traditionally possible only after harvest, which is time-consuming and laborious. This research harnesses high-throughput... M.A. Bari, A. Bakshi, T. Witt, D. Caragea, K. Jagadish, T. Felderhoff