Proceedings
Authors
| Filter results3 paper(s) found. |
|---|
1. Dimensionality Reduction and Similarity Metrics for Predicting Crop Yields in Sparse Data MicroclimatesThis study explores and develops new methodologies for predicting agricultural outcomes, such as crop yields, in microclimates characterized by sparse meteorological data. Specifically, it focuses on reducing the dimensionality in time series data as a preprocessing step to generate simpler and more explainable forecast models. Dimensionality reduction helps in managing large data sets by simplifying the information into more manageable forms without significant loss of information. We explore... L. Huender, M. Everett |
2. Development of a Small-scale Weeding Robot for Inter-plant Areas Using Vision and Rake MechanismIn low-herbicide or herbicide-free farming systems such as those used for medicinal and herbal crops, weed management remains one of the most labor-intensive tasks. Intra-row weeds, which grow between closely spaced crop plants, are particularly difficult to remove using traditional mechanical methods. Manual weeding, although effective, still poses a significant labor burden and limits the scalability despite the high market value of the crops. To address this challenge, we have developed... K. Imaoka |
3. Development of a Small-Scale Weeding Robot for Inter-Plant Areas Using Vision and Rake MechanismIn low-herbicide or herbicide-free farming systems such as those used for medicinal and herbal crops, weed management remains one of the most labor-intensive tasks. Intra-row weeds, which grow between closely spaced crop plants, are particularly difficult to remove using traditional mechanical methods. Manual weeding, although effective, still poses a significant labor burden and limits the scalability despite the high market value of the crops. To address this challenge, we have developed... K. Imaoka |