Attention and Hybrid Loss Guided 2-D Network for Seismic Impedance Inversion
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2023.3262679
Abstract: Deep learning methods, especially convolutional neural networks, achieve state-of-the-art performance on seismic impedance inversion. Most of the methods are based on one-dimensional (1-D) convolution, tending to yield lateral discontinuities of impedance on field data applications.… read more here.
Keywords: network; seismic impedance; inversion; hybrid loss ... See more keywords
Hybrid Loss-Guided Coarse-to-Fine Model for Seismic Data Consecutively Missing Trace Reconstruction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3223421
Abstract: Seismic data are generally sampled irregularly and sparsely along spatial coordinates because economic costs and obstacles hinder the regular arrangement of geophones in the field. Thus, the sampled seismic data often contain missing traces which… read more here.
Keywords: data consecutively; network; hybrid loss; model ... See more keywords
Low-Dose CT Image Denoising with Improving WGAN and Hybrid Loss Function
Sign Up to like & getrecommendations! Published in 2021 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2021/2973108
Abstract: The X-ray radiation from computed tomography (CT) brought us the potential risk. Simply decreasing the dose makes the CT images noisy and diagnostic performance compromised. Here, we develop a novel denoising low-dose CT image method.… read more here.
Keywords: hybrid loss; low dose; dose image; loss function ... See more keywords