Construction Strategies and Experimental Design of the Action Recognition and Optimization System for Gymnasts

This research is dedicated to designing a detailed construction plan for an action recognition and optimization system for gymnasts and making a detailed plan for its subsequent experimental procedures. When the system construction and experiments are still in the preliminary theoretical exploration and preparation stage, through in-depth analysis of aspects such as the establishment of deep learning models, the layout of the interactive interface, and the collaborative architecture of cloud and edge computing, as well as a comprehensive conception of the experimental design. It lays a solid theoretical foundation for the subsequent actual implementation of relevant work, provides a detailed planning blueprint, helps transform this system from a theoretical concept into practical application step by step, and promotes the intelligent transformation in the field of gymnastics training.