The scientist’s investigation covers issues in Algorithm, Seismic wave, Mathematical analysis, Mathematical optimization and Wave equation. His study on Synthetic data is often connected to Data processing as part of broader study in Algorithm. His Seismic wave research is multidisciplinary, incorporating elements of Image registration, Reflection, Normal moveout and Continuation.
The study incorporates disciplines such as Fast marching method, Coordinate system and Optics in addition to Mathematical analysis. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Low-pass filter, Regularization, Inversion and Regression. His research integrates issues of Attenuation and Offset in his study of Wave equation.
His primary areas of study are Algorithm, Mathematical analysis, Artificial intelligence, Extrapolation and Wave equation. Sergey Fomel usually deals with Algorithm and limits it to topics linked to Mathematical optimization and Applied mathematics. His work in Mathematical analysis tackles topics such as Anisotropy which are related to areas like Azimuth.
His Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition. His work deals with themes such as Seismic migration, Seismic wave, Finite difference and Operator, which intersect with Extrapolation. His Wave equation research includes elements of Amplitude and Offset.
His scientific interests lie mostly in Artificial intelligence, Algorithm, Deep learning, Artificial neural network and Convolutional neural network. His work on Fuzzy logic as part of general Artificial intelligence research is frequently linked to Data processing, thereby connecting diverse disciplines of science. His Algorithm study also includes fields such as
His Convolutional neural network study deals with Interpretation intersecting with Surface. The Inversion study combines topics in areas such as Wave equation and Inverse problem. His Mathematical analysis study combines topics from a wide range of disciplines, such as Time domain, Depth conversion and Attenuation.
Sergey Fomel mostly deals with Artificial intelligence, Convolutional neural network, Artificial neural network, Interpretation and Pattern recognition. His study focuses on the intersection of Interpretation and fields such as Surface with connections in the field of Algorithm. His Inverse problem research incorporates themes from Inversion and Wave equation.
His Inversion research includes themes of Amplitude, Extrapolation, Mathematical analysis and Mathematical optimization. His Extrapolation research focuses on subjects like Diffraction, which are linked to Reflection. Sergey Fomel has researched Mathematical analysis in several fields, including Seismic migration and Wave propagation, Optics.
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Applications of plane-wave destruction filters
Angle-domain common-image gathers by wavefield continuation methods
Paul C. Sava;Sergey B Fomel.
Shaping regularization in geophysical-estimation problems
Time-shift imaging condition in seismic migration
Paul Sava;Sergey B Fomel.
Seismic wave extrapolation using lowrank symbol approximation
Sergey B Fomel;Lexing Ying;Xiaolei Song.
Geophysical Prospecting (2013)
FaultSeg3D: Using synthetic data sets to train an end-to-end convolutional neural network for 3D seismic fault segmentation
Xinming Wu;Luming Liang;Yunzhi Shi;Sergey Fomel.
Local seismic attributes
Sergey B Fomel.
Seislet transform and seislet frame
Sergey Fomel;Yang Liu.
Poststack velocity analysis by separation and imaging of seismic diffractions
Sergey B Fomel;Evgeny Landa;M. Turhan Taner.
Madagascar: open-source software project for multidimensional data analysis and reproducible computational experiments
Sergey Fomel;Paul Sava;Ioan Vlad;Yang Liu.
Journal of open research software (2013)
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