Proceedings
Authors
| Filter results2 paper(s) found. |
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1. Generative Modeling Method Comparison for Class Imbalance CorrectionAn image dataset, for use in object detection of hay bales, with over 6000 images of both good and bad hay bales was collected. Unfortunately, the dataset developed a class imbalance, with more good bale images than bad bales. This dataset class imbalance caused the bad bale class to over train and the good bale class to under train, severely impacting precision, and recall. To correct this imbalance and provide a comparison of differing generative modeling methods; three different... B. Vail, Z. Oster, B. Weinhold |
2. Machine Vision in Hay Bale ProductionThe goal of this project is to develop a system capable of real-time detection, pass/fail classification, and location tracking of large square hay bales under field conditions. First, a review of past and current methods of object detection was carried out. This led to the selection of the YOLO family of detectors for this project. The image dataset was collected through help from our sponsor, collection of images from the K-STATE research farm, and images collected from the... B. Vail |