Proceedings
Authors
| Filter results4 paper(s) found. |
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1. Sensing-Based Correlation Analysis of Surface Elevation and Topsoil Depth in Japanese Rice Paddy FieldProper management of soil physical properties is fundamental for stabilizing crop yields and optimizing resource efficiency in large-scale rice paddy production. Among these properties, field surface elevation and topsoil depth (TD) are critical determinants of water management effectiveness and root zone environments. This study conducted a high-resolution grid-based correlation analysis between surface elevation and TD in a 1.4-ha paddy field in Tottori Prefecture, Japan. To overcome the limitations... E. Morimoto, J. Lee, K. Nishida, H. Itoh |
2. Automated Initial Plant Stand Assessment in Bean Crops Using Uav-based Yolov8 DetectionThe use of RGB images acquired by unmanned aerial vehicles (UAVs), combined with artificial intelligence techniques, has increased significantly in recent years for object identification and crop monitoring in agriculture. These technologies enable rapid plant stand count, facilitating decision-making processes. However, limited information is available regarding the optimal flight height for identifying bean plants at early growth stages. Therefore, the objective of this study was to evaluate... G. Valdes Fernandez , G. Lacerda Da Silveira, R. Fernandes Queiroz Alves , T. Costa Barboza, M.C. Arnosti, A. Felipe Dos Santos, W.B. Da Silva, O. Pereira Da Costa |
3. Comparative Analysis of YOLOv3–YOLOv12 Architectures for Automatic Oil Palm Detection in Agricultural MonitoringOil palm (Elaeis guineensis) is considered the most productive oilseed crop worldwide, and Brazil holds one of the greatest global potentials for palm oil production. Efficient monitoring of cultivated areas is therefore essential for proper crop management, enabling the detection of planting gaps, yield estimation, and decision-making support. In this context, computer vision techniques based on deep learning models, particularly those from the YOLO (You Only Look Once) family, have... M.C. Arnosti, A. Felipe Dos Santos, T. Costa Barboza, L.S. Souza Pinto, E. Amaral, G. Lacerda Da Silveira, G. Valdes Fernandez |
4. Evaluation of the Performance of Computer Vision Models in the Detection and Counting of Tomato Plants Infected by Tomato Spotted Wilt Virus (TSWV)Tomato is one of the most economically important vegetable crops worldwide. However, this crop is severely affected by Tomato Spotted Wilt Virus (TSWV), whose transmission occurs mainly through thrips. Thus, identifying infected plants is an important step to reduce the dissemination and infection of healthy plants, reducing economic losses. Computer vision-based models have been widely used in the automated detection of plant diseases. In this context, this work aimed to evaluate the performance... L.S. Souza Pinto, S. . Azevedo, M. . Medeiros, A. Felipe Dos Santos, T. Costa Barboza, M.C. Arnosti, G. Valdes Fernandez , G. Lacerda Da Silveira |