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Found 5 papers, 2 papers with code
Learned 3D volumetric recovery of clouds and its uncertainty for climate analysis
We demonstrate the approach in simulations and on real-world data, and indicate the relevance of 3D recovery and uncertainty to precipitation and renewable energy.
3DeepCT: Learning Volumetric Scattering Tomography of Clouds
We present 3DeepCT, a deep neural network for computed tomography, which performs 3D reconstruction of scattering volumes from multi-view images.
4D Cloud Scattering Tomography
We derive computed tomography (CT) of a time-varying volumetric scattering object, using a small number of moving cameras.
3D Scattering Tomography by Deep Learning with Architecture Tailored to Cloud Fields
We present 3DeepCT, a deep neural network for computed tomography, which performs 3D reconstruction of scattering volumes from multi-view images.
Spatiotemporal tomography based on scattered multiangular signals and its application for resolving evolving clouds using moving platforms
If these rates are used, the paper leads to a representation of the time-varying object, which simplifies 4D CT tomography.
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