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Devine, J
Bouroubi, Y
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Authors
Bouroubi, Y
Bugnet, P
Nguyen-Xuan, T
Bélec, C
Longchamps, L
Vigneault, P
Gosselin, C
Cullop, J
Griffin, T.W
Ibendahl, G
Barnes, E
Shockley, J
Devine, J
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
Topics
Big Data, Data Mining and Deep Learning
Robotics, Guidance and Automation
Decision Support Systems
Type
Oral
Poster
Year
2018
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1. Pest Detection on UAV Imagery Using a Deep Convolutional Neural Network

Presently, precision agriculture uses remote sensing for the mapping of crop biophysical parameters with vegetation indices in order to detect problematic areas, and then send a human specialist for a targeted field investigation. The same principle is applied for the use of UAVs in precision agriculture, but with finer spatial resolutions. Vegetation mapping with UAVs requires the mosaicking of several images, which results in significant geometric and radiometric problems. Furthermore, even... Y. Bouroubi, P. Bugnet, T. Nguyen-xuan, C. Bélec, L. Longchamps, P. Vigneault, C. Gosselin

2. Economics of Swarm Bot Profitability for Cotton Harvest

Improved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine

3. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi