Proceedings
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| Filter results3 paper(s) found. |
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1. Specification Of Data Dimension To Measure The Data Quality On Cotton ProductionThe management of cotton cultivation and agriculture in general, depend on quality data enabling the retrieving of useful information as an aid in decision making related to management techniques and farm management . Part of this task depends intelligible data generated through the processes that make up this segment . Creating means for enabling the classification data is the starting point for making decisions regarding any corrections or adjustments in the mass data . The heterogeneity... C. Santos, A. Hirakawa |
2. Pest Detection on UAV Imagery Using a Deep Convolutional Neural NetworkPresently, 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 |
3. Variety Effects on Cotton Yield Monitor CalibrationWhile modern grain yield monitors are able to harvest variety and hybrid trials without imposing bias, cotton yield monitors are affected by varietal properties. With planters capable of site-specific planting of multiple varieties, it is essential to better understand cotton yield monitor calibration. Large-plot field experiments were conducted with two southeast Missouri cotton producers to compare yield monitor-estimated weights and observed weights in replicated variety trials. Two replications... E. Vories, A. Jones, G. Stevens, C. Meeks |