Panta, M.;                     Thapa, P.J.;                     Hoque, M.T.;                     Niles, K.N.;                     Sloan, S.;                     Flanagin, M.;                     Pathak, K.;                     Abdelguerfi, M.    
        Application of Deep Learning for Segmenting Seepages in Levee Systems. Remote Sens. 2024, 16, 2441.
    https://doi.org/10.3390/rs16132441
    AMA Style
    
                                Panta M,                                 Thapa PJ,                                 Hoque MT,                                 Niles KN,                                 Sloan S,                                 Flanagin M,                                 Pathak K,                                 Abdelguerfi M.        
                Application of Deep Learning for Segmenting Seepages in Levee Systems. Remote Sensing. 2024; 16(13):2441.
        https://doi.org/10.3390/rs16132441
    
    Chicago/Turabian Style
    
                                Panta, Manisha,                                 Padam Jung Thapa,                                 Md Tamjidul Hoque,                                 Kendall N. Niles,                                 Steve Sloan,                                 Maik Flanagin,                                 Ken Pathak,                                 and Mahdi Abdelguerfi.        
                2024. "Application of Deep Learning for Segmenting Seepages in Levee Systems" Remote Sensing 16, no. 13: 2441.
        https://doi.org/10.3390/rs16132441
    
    APA Style
    
                                Panta, M.,                                 Thapa, P. J.,                                 Hoque, M. T.,                                 Niles, K. N.,                                 Sloan, S.,                                 Flanagin, M.,                                 Pathak, K.,                                 & Abdelguerfi, M.        
        
        (2024). Application of Deep Learning for Segmenting Seepages in Levee Systems. Remote Sensing, 16(13), 2441.
        https://doi.org/10.3390/rs16132441