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This project is using computer vision to calculate the respiration rate of lying dairy cows. By analyzing the difference in average pixel intensity in annotated bounding boxes and performing Fast Fourier Transform to select the most prevalent data, this model predicts the number of times a cow breathed in a 30-second interval.
A Python-based simulation model for studying the dynamics of superspreader events in epidemic outbreaks. This project enables analysis and visualization of transmission patterns, helping to understand the impact of superspreaders on disease spread.