Computer aided technology based on graph sample and aggregate attention network optimized for soccer teaching and training

Abstract

Football is the most popular game in the world and has significant influence on various aspects including politics, economy and culture. The experience of the football developed nation has shown that the steady growth of youth football is crucial for elevating a nation's overall football proficiency. It is essential to develop techniques and create strategies that adapt to their individual physical features to resolve the football players’ problem of lacking exercise in various topics. In this manuscript, Computer aided technology depending on the Graph Sample and Aggregate Attention Network Optimized for Soccer Teaching and Training (CAT-GSAAN-STT) is proposed to improve the efficiency of Soccer teaching and training effectively. The proposed method contains four stages, like data collection, data preprocessing, prediction and optimization. Initially the input data are collected by Microsoft Kinect V2 smart camera. Then the collected data are preprocessed by using Improving graph collaborative filtering. After preprocessing the data is given for motion recognition layer here prediction is done using Graph Sample and Aggregate Attention Network (GSAAN) for improving the effectiveness of Soccer Teaching and Training. To enhance the accuracy of the system, the GSAAN are optimized by using Artificial Rabbits Optimization. The proposed CAT-GSAAN-STT method is executed in Python and the efficiency of the proposed technique is examined with different metrics, like accuracy, computation time, learning activity analysis, student performance ratio and teaching evaluation analysis. The simulation outcomes proves that the proposed technique attains provides28.33%, 31.60%, 25.63% higherRecognition accuracy and33.67%, 38.12% and 27.34%lesser evaluation time while compared with existing techniques like computer aided teaching system based upon artificial intelligence in football teaching with training (STT-IOT-CATS), Computer Aided Teaching System for Football Teaching and Training Based on Video Image (CAT-STT-VI) and method for enhancing the football coaching quality using artificial intelligence and meta verse-empowered in mobile internet environment (SI-STQ-AI-MIE) respectively.