most citedDeep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes

5 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.GA20223 cited

Reconstructing and Classifying SDSS DR16 Galaxy Spectra with Machine-Learning and Dimensionality Reduction Algorithms

Felix Pat, Stéphanie Juneau, Vanessa Böhm +6

Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic prop…

cs.CV2022

SAR-based landslide classification pretraining leads to better segmentation

Vanessa Böhm, Wei Ji Leong, Ragini Bal Mahesh +5

Rapid assessment after a natural disaster is key for prioritizing emergency resources. In the case of landslides, rapid assessment involves determining the extent of the area affec…

eess.SP20225 cited

Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes

Vanessa Boehm, Wei Ji Leong, Ragini Bal Mahesh +5

With climate change predicted to increase the likelihood of landslide events, there is a growing need for rapid landslide detection technologies that help inform emergency response…

astro-ph.IM2022

Impact of COVID-19 on Astronomy: Two Years In

Vanessa Böhm, Jia Liu

We study the impact of the COVID-19 pandemic on astronomy using public records of astronomical publications. We show that COVID-19 has had both positive and negative impacts on res…

astro-ph.CO20201 cited

MADLens, a python package for fast and differentiable non-Gaussian lensing simulations

Vanessa Böhm, Yu Feng, Max E. Lee +1

We present MADLens a python package for producing non-Gaussian lensing convergence maps at arbitrary source redshifts with unprecedented precision. MADLens is designed to achieve h…