Deep Learning Seismic Inversion Based on Prestack Waveform Datasets
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3195858
Abstract: Prediction of elastic parameters (e.g., P-, S-wave velocity, and density) from observed seismic data is one of the most common means of reservoir characterization. Recently, deep learning (DL), as a data-driven approach, has been attracting… read more here.
Keywords: inversion; seismic inversion; training dataset; data driven ... See more keywords
Small training dataset convolutional neural networks for application-specific super-resolution microscopy
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Biomedical Optics"
DOI: 10.1117/1.jbo.28.3.036501
Abstract: Significance Machine learning (ML) models based on deep convolutional neural networks have been used to significantly increase microscopy resolution, speed (signal-to-noise ratio), and data interpretation. The bottleneck in developing effective ML systems is often the… read more here.
Keywords: microscopy; super resolution; training dataset; denseed blocks ... See more keywords