<ul><li>A computer vision-based system has been developed for detecting and tracking ears of corn in an image sequence.</li><li>The system accurately detects, tracks, and predicts the ear's orientation, providing insights into the plant's health and development.</li><li>Using an object detector with keypoint detection, the algorithm achieved a 90 percent accuracy in ear detection.</li><li>The system has the potential to save time and improve efficiencies in maize production.</li></ul>

Corn Ear Detection and Orientation Estimation Using Deep Learning

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