About this Research Topic
Recently, an extensive range of digital signal processing, image processing, and pattern recognition applications have been getting an increasing interest in geoscience research. The purpose of this Research Topic is to highlight the potential of the latest methods and algorithms that are being used to extract useful information in different geoscience fields, particularly in use of applications that cannot be inferred using the conventional analysis tools.
This Research Topic aims at illustrating the potential of numerical processing methods, including:
• Linear/nonlinear time-series analysis;
• Statistical methods;
• (Multi)fractal analysis;
• Spectral analysis using Fourier/wavelet transforms;
• Machine learning & artificial intelligence algorithms.
We encourage scientists to submit contributions related to the application of these techniques in different fields of geosciences, including:
• Geophysics (seismic, gravity/magnetic, electromagnetism/magneto-telluric, etc.),
• Mining applications,
• Hydrogeology,
• Geodesy/topography,
• And more Geological applications.
This Research Topic aims at illustrating the potential of numerical processing methods, including:
• Linear/nonlinear time-series analysis;
• Statistical methods;
• (Multi)fractal analysis;
• Spectral analysis using Fourier/wavelet transforms;
• Machine learning & artificial intelligence algorithms.
We encourage scientists to submit contributions related to the application of these techniques in different fields of geosciences, including:
• Geophysics (seismic, gravity/magnetic, electromagnetism/magneto-telluric, etc.),
• Mining applications,
• Hydrogeology,
• Geodesy/topography,
• And more Geological applications.
Keywords: signal processing, image processing, pattern recognition, geosciences
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
