Proceedings
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| Filter results2 paper(s) found. |
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1. Field-scale Nitrogen Recommendation Tools for Improving a Canopy Reflectance Sensor AlgorithmNitrogen (N) rate recommendation tools are utilized to help producers maximize grain yield production. Many of these tools provide recommendations at field scales but often fail when corn N requirements are variable across the field. This may result in excess N being lost to the environment or producers receiving decreased economic returns on yield. Canopy reflectance sensors are capable of capturing within-field variability, although the sensor algorithm recommendations may not always be as accurate... C.J. Ransom, M. Bean, N. Kitchen, J. Camberato, P. Carter, R. Ferguson, F. Fernandez, D. Franzen, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan |
2. Develpoment of Bagged Guava Quality Grading System Using Image Recognition and Generative Adversarial Networks(GANS)Taiwan’s warm climate and abundant sunlight make it highly suitable for guava cultivation, making guava an important economic crop. However, current quality grading still relies on manual inspection, which is labor-intensive, inconsistent, and affected by bagging practices. To address this, we propose an automatic grading system using deep learning and generative adversarial networks. The framework collects images of bagged and bare guavas, applies YOLOv9 for fruit detection and background... C. Chang |