@article{MAKHILLAJIT2005424856,
    title = {Radarsat-1 Sar Surface Current Detection By Neural Network},
    journal = {Asian Journal of Information Technology},
    volume = {4},
    number = {2},
    pages = {147-151},
    year = {2005},
    issn = {1682-3915},
    doi = {ajit.2005.147.151},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2005.147.151},
    author = {Maged Marghany},
    keywords = {},
    abstract = {This study introduces a new approach for utilizing the neural network for surface current simulation from RADARSAT-1 SAR image. The neural network input is a vector containing the values of the RADARSAT-1 SAR image intensity gradients. In this study, a single feed forward -propagation neural network was utilized to estimate the Doppler frequency shift in order to determine the surface current pattern along RADARSAT-1 SAR image. It is found that, the neural network outperformed conventional regression technique in modeling surface current velocity and their directions. The RMSE detected from NN model was 0.18 m/s. The reduction of the amount of the errors is due to good performance of regression model.}
    }