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| Filter results3 paper(s) found. |
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1. Weeds Detection By Ground-level Hyperspectral ImagingWeeds are a severe pest in agriculture, causing extensive yield loss. Weed control of grass and broadleaf weeds is commonly performed by applying selective herbicides homogeneously all over the field. As presented in several studies, applying the herbicide only where needed has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically... U. Shapira , I. Herrmann, A. Karnieli, D.J. Bonfil |
2. Ground Level Hyperspectral Imagery For Weeds Detection In Wheat FieldsWeeds are a severe pest in agriculture resulting in extensive yield loss. Applying precise weed control has economical as well as environmental benefits. Combining remote sensing tools and techniques with the concept of precision agriculture has the potential to automatically locate and identify weeds in order to allow precise control. The objective of the current work is to detect annual... D.J. Bonfil, U. Shapira, A. Karnieli, I. Herrmann, S. Kinast |
3. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical DataBayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri |