Research on Optimization of Network TV Automation Testing Algorithm Based on Deep Learning
The article proposes a new network television automation testing algorithm optimization scheme based on deep learning.This scheme adopts deep learning techniques such as convolutional neural networks and reinforcement learning to achieve accurate recognition of UI controls and dynamic test case generation,effectively solving problems such as high system complexity and low interface accessibility support.The article introduces the specific implementation details and optimization strategies of the algorithm,and demonstrates its effectiveness and superiority through a large number of experiments.
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