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Mouazen, D
Holthaus, D
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Authors
Whattoff, D
Mouazen, D
Waine, D
Spiesman, B
Grijalva, I
Holthaus, D
McCornack, B
Topics
Proximal Sensing in Precision Agriculture
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2016
2024
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Filter results2 paper(s) found.

1. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.

Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement.  However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (VDT)... D. Whattoff, D. Mouazen, D. Waine

2. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV Imagery

Pollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack