Proceedings
Authors
| Filter results3 paper(s) found. |
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1. Identifying Critical Landscape Areas for Precision Conservation in the Minnesota River BasinThe Minnesota River Basin generates a disproportionately high amount of total suspended sediments to the Upper Mississippi River Basin. Many reaches in the Minnesota River Basin have impaired water quality due to turbidity. Critical landscapes can be divided into depressional areas, riparian areas, highly erodible lands, and areas susceptible to ephemeral gullies or ravines. Geographic Information Systems (GIS) were utilized, and terrain analysis was conducted using digital elevation models in... J. Galzki, J. Nelson, D. Mulla |
2. Weed Detection Among Crops by Convolutional Neural Networks with Sliding WindowsOne of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neural... K. Kantipudi, C. Lai, C. Min, R.C. Chiang |
3. Using On-the-Go Soil Sensors to Assess Spatial Variability within the KS Wheat Breeding ProgramIn plant breeding the impacts of genotype by environment interactions and the challenges to quantify these interactions has long been recognized. Both macro and microenvironment variations in precipitation, temperature and soil nutrient availability have been shown to impact breeder selections. Traditionally, breeders mitigate these interactions by evaluating genotype performance across varying environments over multiple years. However, limitations in labor, equipment and seed availably can limit... B. Evers, M. Rekhi, G. Hettiarachchi, S. Welch, A. Fritz, P.D. Alderman, J. Poland |