Proceedings
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| Filter results4 paper(s) found. |
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1. The Cost Of Dependence Upon GPS-enabled Navigation TechnologiesThe adoption of global positioning system (GPS) technology to fine-tune agricultural field operations over the last decade has been unprecedented relative to other agricultural technologies. Resultantly, as agricultural machinery size and capacity increased, field operations have become much more precise due to the synergistic relationship between farm machinery and GPS-enabled guidance technology. With increased dependence upon GPS technology, one must ask “What are the risks associated... C. Lee, T. Griffin |
2. Automatic Detection And Mapping Of Irrigation System Failures Using Remotely Sensed Canopy Temperature And Image ProcessingToday there is no systematic way to identify and locate failures of irrigation systems mainly because of the labor costs associated with locating the failures. The general aim of this study was to develop an airborne thermal imaging system for semi - automatic monitoring and mapping of irrigation system failures, specifically, of leaks and clogs. Initially, leaks and clogs were simulated by setting controlled trials in table grapes vineyards and olive groves. Airborne thermal... V. Alchanatis, Y. Cohen, M. Sprinstin, A. Cohen, I. Zipori, A. Dag, A. Naor |
3. Comparison Of The Variable Potassium Fertilization On The Light And Heavy SoilsIntroduction. Determination of the spatial variability of the nutrient levels in soil facilitated adaptation of the fertilizer doses to the soluble forms availability. Nowadays, an increasing use of this method of the fertilizer application is observed, with this being associated with both economical and environmental advantages, as well as, with growing assortment of the purpose-built agricultural instrumentation. An accurate determination of the spatial distribution... P. Grocholski, P. Stepien, G. Kulczycki, A. Michalski |
4. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and VisionAdvancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor. While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi |