Advances in remote sensing technology have led to the capture of massive amounts of data.
"No-till" and cover cropping are often identified as the leading simple, best management practices for carbon sequestration in agriculture.
Next, we construct our proposed spatiotemporal architecture, which combines a UNet with a convolutional LSTM layer, to accurately detect regions of the field showing NDS; this approach has an impressive IOU score of 0. 53.
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially for the semantic segmentation task associated with our challenge dataset.
Central to all machine learning algorithms is data representation.
Sporting events are extremely complex and require a multitude of metrics to accurate describe the event.