<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, the road visibility detection method based on video has been paid more and more attention. It has overcome the deficiency of laser visibility meter to some extent. Deep learning has a good effect in image processing and analysis. This paper firstly analyzes the current situation of deep learning, and then compares DenseNet and ResNet to propose a visibility estimation model based on deep DenseNet. The model firstly integrates airport video data and visibility data. Secondly, the DenseNet algorithm is used to automatically extract the features of the airport data set. Finally, Softmax classifier is constructed to evaluate the visibility accuracy. They reduce the problem of disappearing gradient, enhance feature propagation, encourage functional reuse, and greatly reduce the number of parameters, well train the deep model, has a good visibility estimation effect. On this basis, this paper based on Canny operator lane dividing line extraction edge extraction and visibility analysis based on edge detection, and do the corresponding test. Finally, a video visibility analysis model based on Kalman filter is built based on the given data, and Gaussian process regression model is used to predict the fog change trend.</p>
</abstract>

In recent years, the road visibility detection method based on video has been paid more and more attention. It has overcome the deficiency of laser visibility meter to some extent. Deep learning has a good effect in image processing and analysis. This paper firstly analyzes the current situation of deep learning, and then compares DenseNet and ResNet to propose a visibility estimation model based on deep DenseNet. The model firstly integrates airport video data and visibility data. Secondly, the DenseNet algorithm is used to automatically extract the features of the airport data set. Finally, Softmax classifier is constructed to evaluate the visibility accuracy. They reduce the problem of disappearing gradient, enhance feature propagation, encourage functional reuse, and greatly reduce the number of parameters, well train the deep model, has a good visibility estimation effect. On this basis, this paper based on Canny operator lane dividing line extraction edge extraction and visibility analysis based on edge detection, and do the corresponding test. Finally, a video visibility analysis model based on Kalman filter is built based on the given data, and Gaussian process regression model is used to predict the fog change trend.

Research on Visibility Estimation Model Based on DenseNet

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Research on Visibility Estimation Model Based on DenseNet"}

In recent years, the road visibility detection method based on video has been paid more and more attention. It has overcome the deficiency of laser visibility...

Research on Visibility Estimation Model Based on DenseNet

Published Online: May 31, 2023

Page range: 10 - 17

DOI: https://doi.org/10.2478/ijanmc-2023-0042

Keywords
Densenet, Visibility Estimation, Softmax Classifier

© 2023 Guang Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Research on Visibility Estimation Model Based on DenseNet

Published Online: May 31, 2023

Page range: 10 - 17

DOI: https://doi.org/10.2478/ijanmc-2023-0042

KeywordsDensenet, Visibility Estimation, Softmax Classifier

© 2023 Guang Li et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Keywords
Densenet, Visibility Estimation, Softmax Classifier