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Exploring the Potential of AI for Swim Technique Evaluation and Athlete-Centered Coaching
Get PDFThis project explores the use of AI-powered video analysis to simulate elite-level coaching in butterfly stroke technique. Using Google’s Gemini 2.5, the goal of the project is to determinewhether a large multimodel, trained on technique videos of elite swimmers, can generate detailed and personalized feedback that mirrors the insight of a well-informed human swim coach. Training videos featuring Olympic-level butterfly swimmers were used to establish an internal reference model of an ideal butterfly technique. The model was then presented with videos of collegiate swimmers and prompted to deliver coaching-style feedback. Overall, this project demonstrates the potential for AI systems to support accessible athletic development, offering real-time, technical feedback based upon researched coaching science and elite athletic performance
A Comparison of Insect Succession in Decomposing Quercus coccinea and Magnolia stellata Leaf Litter
No full textThe Effects of Elevation on the American Pika (Ochotona princeps) Microbiome in Glacier National Park
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Tannase Activity of Bacteria on Quercus coccinea Leaves Contributes to the Breakdown of Tannins
No full textPosterior regeneration is similar across Lumbriculus variegatus exposed to sodium chloride, calcium chloride, and freshwater
No full textA Total Modernity and Alternative Avant-Garde Art in China
Get PDFIn this paper, Gao discusses twentieth century Chinese avant-garde in two major periods: the avant-garde of the 1920s and 1930s; and the contemporary avant-garde of Post-Mao era - the 1980s and 1990s. (Nicole Wang \u2726)https://digital.kenyon.edu/zhoudocs/1514/thumbnail.jp