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Ellixson, A
Banerjee, M
Bakshi, A
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Authors
Banerjee, M
Dutta, S
Bhuiya, G
Malik, G
Maiti, D
Goeringer, P
Ellixson, A
Moyle, J
Ellixson, A
Goeringer, P
Griffin, T
Bari, M.A
Bakshi, A
Witt, T
Caragea, D
Jagadish, K
Felderhoff, T
Pramanik, S
Choton, J
Topics
Precision Nutrient Management
Unmanned Aerial Systems
Standards & Data Stewardship
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2014
2016
2024
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Filter results4 paper(s) found.

1. Precision Nutrient Management Through Use Of LCC And Nutrient Expert In Hybrid Maize Under Laterite Soil Of India

Nutrient management has played a crucial role in achieving self sufficiency in food grain production. Energy crisis resulted in high price index of chemical fertilizers. Coupled with their limited production, fertilizer cost, soil health, sustainability and pollution have gave rise to interest in precision nutrient management tools. Field experiment was conducted to study the effect of variety and nutrient management on the growth and productivity of maize under lateritic belt of West Bengal... M. Banerjee, S. Dutta, G. Bhuiya, G. Malik, D. Maiti

2. Privacy Issues and the Use of UASs/Drones in Maryland

 According to the Federal Aviation Administration (FAA), the lawful use of Unmanned Aerial Vehicles (UAV), also known as Unmanned Aircraft Systems (UAS), or more commonly as drones, are currently limited to military, research, and recreational applications. Under the FAA’s view, commercial uses of drones are illegal unless approved by the Federal government.  This will change in the future.  Congress authorized the FAA to develop regulations for the use of drones by private... P. Goeringer, A. Ellixson, J. Moyle

3. Ownership and Protections of Farm Data

Farm data has been a contentious point of debate with respect to ownership rights and impacts when access rights are misappropriated. One of the leading questions farmers ask deals with the protections provided to farm data. Although no specific laws or precedence exists, the possibility of trade secret is examined and ramifications for damages discussed. Farm management examples are provided to emphasize the potential outcomes of each possible recourse for misappropriating farm data. ... A. Ellixson, P. Goeringer, T. Griffin

4. 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