Abstract: Seismic denoising is a fundamental and critical task in seismic data processing. Aiming at solving the computational complexity of 3-D seismic data processing, we propose a novel data-driven ...
Abstract: High-quality and diverse datasets are crucial for supervised learning in industrial defect detection, yet collecting such data remains challenging. Synthetic data generation offers a ...
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