From post

Oil Slicks Detection From Polarimetric Data Using Stochastic Distances Between Complex Wishart Distributions.

, , , , и . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 10 (2): 463-477 (2017)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

Oil Slicks Detection From Polarimetric Data Using Stochastic Distances Between Complex Wishart Distributions., , , , и . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 10 (2): 463-477 (2017)Oil slicks detection using a polarimetric region classifier., , , , и . IGARSS, стр. 3239-3242. IEEE, (2015)Intelligent hybrid system for dark spot detection using SAR data., , , , и . Expert Syst. Appl., (2017)The contribution of ASTER, CBERS, R99/SIPAM e OrbiSAR-1 data to improve the oceanic monitoring., , , , и . IGARSS, стр. 994-996. IEEE, (2007)Development and Application of Predictive Models to Distinguish Seepage Slicks from Oil Spills on Sea Surfaces Employing SAR Sensors and Artificial Intelligence: Geometric Patterns Recognition under a Transfer Learning Approach., , , , , , , и . Remote. Sens., 15 (6): 1496 (марта 2023)Improved Classification Models to Distinguish Natural from Anthropic Oil Slicks in the Gulf of Mexico: Seasonality and Radarsat-2 Beam Mode Effects under a Machine Learning Approach., , , , , , и . Remote. Sens., 13 (22): 4568 (2021)