Proceedings
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| Filter results5 paper(s) found. |
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1. A Low Cost, Modular Robotics Tool Carrier for Precision Agriculture ResearchCurrent research within agricultural crop production focus on using autonomous robot technology to optimize the production efficiency, enhance sustainability and minimize tedious, monotonous and wearing tasks. But progress is slow partly... A. Bøgild, S.H. Nielsen, N.J. Jacobsen, C.L. Jaeger-hansen, R.N. Jørgensen, K. Jensen, O.J. Jørgensen |
2. Capturing, Demonstrating And Delivering Value From Integrating Real-Time On-Farm Sensing With External Information FlowsThe requirement for significant productivity gains in the agricultural sector is undeniable. Sustainable, viable industries must be capable of consistently producing a margin above the base costs of production. This is particularly challenging for the extensive grazing enterprises in Australia as the operating environment has become increasingly complex, dynamic and challenging and there is a continual and increasing need to demonstrate improved efficiency to the wider community... G. Bishop-hurley, L. Overs, S. Brosnan, A. Krumpholz, D. Henry |
3. Modelling 'Concord' Berry Weight DynamicsThe growth and development of Concord (Vitis labruscana Bailey) depends on internal and external factors. As a result, both vegetative and reproductive cycles of Concord vary based on growing season and vine status. Fresh berry weight also fluctuates depending on the growing season and location of the vineyard. Knowledge of berry weight dynamics across growing season is essential to accurately predict final yield at harvest based on early season crop estimates. The main objective of this study... G. Badr, T.R. Bates |
4. Late Season Imagery for Harvest ManagementThe overall objective of this project was to preliminarily assess the use of UAV-based thermal imagery to sense harvest-related factors. Results suggested that thermal imagery can be used to detect areas of high grain moisture content late in the harvest season. Time periods closer to physiological maturity were less likely to show significant differences in thermal imagery data. Additional research is needed to determine if moisture content trends with other measurable quantities... J. Ward, G. Roberson, R. Phillips |
5. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data AugmentationDigital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier |