Noise suppression is an essential step in many seismic processing workflows. A portion of
this noise, particularly in land datasets, presents itself as random noise. In recent years …

We propose to invert reservoir porosity from poststack seismic data using an innovative
approach based on deep-learning methods. We develop an unsupervised approach to …

Background Anxiety is considered one of the most common pathologies that people go
through frequently, this being the main cause of illness and disability in students since it is …

Firn densification profiles are an important parameter for ice‐sheet mass balance and
palaeoclimate studies. One conventional method of investigating firn profiles is using …

Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences
asynchronously. Recovering brightness from events is appealing since the reconstructed …

Seismic acoustic impedance inversion (SAII) aims at recovering the subsurface impedance
to achieve lithology interpretation. However, its ill-posedness and nonlinearity pose a great …

Many areas of machine learning and science involve large linear algebra problems, such as
eigendecompositions, solving linear systems, computing matrix exponentials, and trace …

Deep-image prior (DIP) is a novel approach to solving ill-posed inverse problems whose
solution is parameterized with an untrained deep neural network and cascaded with the …

Tomography is a powerful tool for reconstructing the interior of an object from a series of
projection images. Typically, the source and detector traverse a standard path (eg, circular …

In Australia, hailstorms present considerable public safety and economic risks, where they
are considered the most damaging natural hazard in terms of annual insured losses …