Automatic understanding and analysis of digital video media content
The article investigates the application of deep convolutional neural networks based on L2 regularization optimization in automatic understanding and analysis of digital video media content.Specifically,the article analyzed the basic principles of DCNN and introduced L2 regularization method to optimize the method.In the experimental section,the YouTube VOS dataset was used to validate and compare the method.The F1 score and intersection to union ratio index were used to evaluate the improvement effect of the optimization method compared to standard DCNN.The experimental results show that this method has achieved excellent results in video object segmentation tasks,verifying the effectiveness of L2 regularization in deep learning model optimization.
digital videovideo analysisdeep convolutional neural networkregularization
万方数据
维普
