Search Results for author:
Found 2 papers, 1 papers with code
End-to-end deep learning for directly estimating grape yield from ground-based imagery
The object detection model was trained on hand-labeled images to localize grape bunches, and either bunch count or pixel area was summed to correlate with grape yield.
Enlisting 3D Crop Models and GANs for More Data Efficient and Generalizable Fruit Detection
To enable more data efficient and generalizable neural network models in agriculture, we propose a method that generates photorealistic agricultural images from a synthetic 3D crop model domain into real world crop domains.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
