Undergraduate Research Intern
During my Summer 2024 internship, I developed and fine-tuned a YOLOv8 object detection and segmentation model aimed at accurately identifying and segmenting wheat fields. I successfully achieved 82% accuracy for object detection and 84% for segmentation, optimizing the model for real-world agricultural applications. Additionally, I worked with multispectral and RGB imaging data to extract key crop features, calculating essential vegetative indices like the Soil Crop Index and Green Normalized Difference Index (GNDI) to assess crop health. By applying machine learning techniques to analyze these features, I contributed to a more accurate prediction of field conditions, supporting data-driven decision-making in agricultural practices.