Proceedings
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| Filter results6 paper(s) found. |
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1. Melon Classification and Segementation Using Low Cost Remote Sensing Data DronesObject recognition represents currently one of the most developing and challenging areas of the Computer Vision. This work presents a systematic study of various relevant parameters and approaches allowing semi-automatic or automatic object detection, applied onto a study case of melons on the field to be counted. In addition it is of a cardinal interest to obtain the quantitative information about performance of the algorithm in terms of metrics the suitability whereof is determined by the final... T. Zhao, Y. Chen, J. Franzen, J. Gonzalez, Q. Yang |
2. Almond Canopy Detection and Segmentation Using Remote Sensing Data DronesThe development of Unmanned Aerial System (UAV) makes it possible to take high resolution images of trees easily. These images could help better manage the orchard. However, more research is necessary to extract useful information from these images. For example, irrigation schedule and yield prediction both rely on accurate measurement of canopy size. In this paper, a workflow is proposed to count trees and measure the canopy size of each individual tree. The performances of three different methods... T. Zhao, M. Cisneros, Y. Chen, Q. Yang, Y. Zhang |
3. Use of a Cropping System Model for Soil-specific Optimization of Limited WaterIn the arena of modern agriculture, system models capable of simulating the complex interactions of all the relevant processes in the soil-water-plant- atmosphere continuum are widely accepted as potential tools for decision support to optimize crop inputs of water to achieve location specific yield potential while minimizing environmental (soil and water resources) impacts. In a recent study, we calibrated, validated, and applied the CERES-Maize v4.0 model for simulating limited-water irrigation... L.R. Ahuja, S.A. Saseendran, L. Ma, D.C. Nielsen, T.J. Trout, A.A. Andales, N.C. Hansen |
4. A Tree Planting Site-Specific Fumigant Applicator for Orchard CropsThe goal of this research was to use recent advances in the global positioning system and computer technology to apply just the right amount of fumigant where it is most needed (i.e., in the neighborhood of each tree planting site or tree- planting-site-specific application) to decrease the incidence of replant disease, and achieve the environmental and economical benefits of reducing the application of these toxic chemicals. In the first year of this study we retrofitted a chemical applicator... S.K. Upadhayaya, V. Udompetaikul, M.S. Shafii, G.T. Browne |
5. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean YieldThe ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van Vliet |
6. Performance of Autonomous Navigation in an Agricultural Tractor Using Pure Pursuit Control and Dubins Path PlanningAutopilot systems in agricultural machinery are primarily designed to ensure accurate tracking of predefined routes. However, their performance is strongly influenced by the internal parameters of the control algorithms employed, which may vary according to operational conditions. In this context, computational simulations constitute a valuable tool for investigating these interactions and identifying optimal operating configurations. This study evaluates an autopilot system based on the Pure... J.D. Baltazar, A.L. Coelho, L. De Arruda Viana, A.D. Brandão, D.S. Valente, M.R. Furtado Jr |