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20172025
most citedWhich picker fits my data? A quantitative evaluation of deep learning based seismic pickers

213 citations

Showing 2021Show all

5 papers · 1 filter

cs.CV2021★ 21 cited

Marine Bubble Flow Quantification Using Wide-Baseline Stereo Photogrammetry

Mengkun She, Tim Weiß, Yifan Song +3

Reliable quantification of natural and anthropogenic gas release (e.g.\ CO, methane) from the seafloor into the water column, and potentially to the atmosphere, is a challengin…

physics.geo-ph2021★ 14 cited

Impacts of peak-flow events on hyporheic denitrification potential

Tanu Singh, Shubhangi Gupta, Gabriele Chiogna +2

Subsurface flows, particularly hyporheic exchange fluxes, driven by streambed topography, permeability, channel gradient and dynamic flow conditions provide prominent ecological se…

physics.geo-ph2021★ 213 cited

Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers

Jannes Münchmeyer, Jack Woollam, Andreas Rietbrock +10

Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significant…

cs.SE2021★ 17 cited

Prototyping Autonomous Robotic Networks on Different Layers of RAMI 4.0 with Digital Twins

Alexander Barbie, Wilhelm Hasselbring, Niklas Pech +3

In this decade, the amount of (industrial) Internet of Things devices will increase tremendously. Today, there exist no common standards for interconnection, observation, or the mo…

cs.SE2021★ 64 cited

Developing an Underwater Network of Ocean Observation Systems with Digital Twin Prototypes -- A Field Report from the Baltic Sea

Alexander Barbie, Niklas Pech, Wilhelm Hasselbring +8

During the research cruise AL547 with RV ALKOR (October 20-31, 2020), a collaborative underwater network of ocean observation systems was deployed in Boknis Eck (SW Baltic Sea, Ger…