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E-sports analysis data acquisition algorithm based on convolutional neural network

机译:基于卷积神经网络的电子竞技分析数据采集算法

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摘要

At present, e-sports has become one of the most important industries. How to analyze e-sports data has become an urgent problem to be solved. Currently, some hot competition items do not provide data interfaces, so that the training set required for data analysis cannot be directly and accurately acquired. Data can only be obtained by watching video games in person. This method is obviously inefficient and the accuracy cannot be guaranteed. This paper proposes a data acquisition algorithm based on convolutional neural network algorithm. It also introduces transfer learning, improves the sample training method and data acquisition method, and finally solves the problem of data acquisition. According to the test, this algorithm achieves about 91% accuracy.
机译:目前,电子竞技已经成为最重要的产业之一。如何分析电子竞技数据已成为亟待解决的问题。当前,一些热门比赛项目不提供数据接口,因此无法直接,准确地获取数据分析所需的训练集。只能通过亲自观看视频游戏来获取数据。这种方法显然效率低下,无法保证准确性。提出了一种基于卷积神经网络算法的数据采集算法。还介绍了迁移学习,改进了样本训练方法和数据采集方法,最终解决了数据采集问题。根据测试,该算法可达到约91%的精度。

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