In hazy weather,visibility detection methods based on image processing are still under continuous research,and the accuracy of visibility estimation is dependent on the accuracy of visibility estimation There is room for improvement.Based on big data,this paper improves VGG convolutional neural network to extract features of video data and uses Adam for algorithm optimization to fully mine surveillance video data information,so as to achieve the purpose of improving accuracy and reducing equipment cost.Compared with ResNet,this method makes full use of the spatio-temporal information of video data,and shows higher precision and accuracy in the prediction process.This study provides a reference for improving the effectiveness of airport visibility prediction.
关键词
能见度预测/卷积神经网络/机场监控视频
Key words
visibility forecast/convolutional neural network/airport surveillance video
维普
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