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| Filter results7 paper(s) found. |
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1. AGTECH CHILE: an Outreach and Technology Transfer Platform for Closing Gaps in Emerging Chilean Precision Agriculture CompaniesPrecision agriculture (PA) is being developed in Chile since 1997. Today there are approximately 20 companies providing products and services in PA at different levels. Most of them are young entrepreneurships which have important knowledge gaps, particularly on technology basis and data management to transform them into useful information. In order to help closing some of the gaps, and contributing to the development of an innovation ecosystem, an extension proposal was developed, which... R.A. Ortega, P. Trebilcock |
2. Using Prescription Maps for in Field Evaluations of Parameteres Affecting Spraying Accuracy of Self-propelled SprayerWeed presence continues to reemerge year over year, chemical costs continue to increase, and chemical usage continuing to face increasing government oversight, are just a few of the challenges that site-specific weed management intends to address by minimizing wasted application of chemicals and reducing environmental load of active ingredients. Thus, sprayer system manufacturers have developed precision spray systems that allow the individual spray nozzles to be controlled precisely. These spray... J. Mayer, P. Flores, J. Stenger |
3. Scaling Up Window-based Regression for Crop-row DetectionCrop-row detection is a central element of weed detection and agricultural image processing tasks. With the increased availability of high-resolution imagery, a precise locating of crop rows is becoming practical in the sense that the necessary data are commonly available. However, conventional image processing techniques often fail to scale up to the data volumes and processing time expectations. We present an approach that computes regression lines over... A.M. Denton, G.E. Hokanson, P. Flores |
4. Assessment of Goss Wilt Disease Severity Using Machine Learning Techniques Coupled with UAV ImageryGoss Wilt has become a common disease in corn fields in North Dakota. It has been one of the most yield-limiting diseases, causing losses of up to 50%. The current method to identify the disease is through visual inspection of the field, which is inefficient, and can be subjective, with misleading results, due to evaluator fatigue. Therefore, developing a reliable, accurate, and automated tool for assessing the severity of Goss's Wilt disease has become a top priority. The use of unmanned... A. Das, P. Flores, Z. Zhang , A. Friskop, J. Mathew |
5. Computer Vision by UAVs for Estimate Soybean Population Across Different Physiological Growth Stages and Sowing SpeedsSoybean (Glycine max (Linnaeus) Merrill) production in the United States plays a crucial role in agriculture, occupying a considerable amount of cultivated land. However, the costs associated with soybean production have shown a notable increase in recent years, with seed-related expenses accounting for a significant proportion of the total. This increase in costs is attributed to a number of factors, including the introduction of patented and protected genetic traits, as well as inflationary... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. Deri setiyono, S. campos |
6. Optimizing Soybean Management with UAV RGB and Multispectral Imagery: a Neural Network Method and Image ProcessingPrecision agriculture (PA) has emerged as a fundamental approach in contemporary agricultural management, aimed at maximizing efficiency in the use of resources and improving crop productivity. The transition to so-called "agriculture 4.0" represents a revolution in the way technology is applied in the field, with an emphasis on digital and automated solutions such as UAVs (Unmanned Aerial Vehicles). These devices offer new capabilities for capturing high-resolution images, enabling... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. deri setiyono, S. Campos |
7. North Dakota State University - Sponsor Presentation... L. Schumacher, P. Flores, R. Sun, A. Reinholz |