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Published in 2022 at "Journal of Aerosol Science"
DOI: 10.1016/j.jaerosci.2022.105977
Abstract: Atmospheric aerosols have a major influence on the earth’s climate and public health. Hence, studying their properties and recovering them from light scattering measurements is of great importance. State of the art retrieval methods such…
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Keywords:
neural networks;
scattering measurements;
using invertible;
aerosol properties ... See more keywords
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Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3199210
Abstract: As recognized, the ground-truth multispectral (MS) images possess the complementary information (e.g., high-frequency components) of low-resolution (LR) MS images, which can be considered as privileged information to alleviate the spectral distortion and insufficient spatial texture…
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Keywords:
network;
pan;
ground truth;
pan sharpening ... See more keywords
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Published in 2021 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2021.3129537
Abstract: We introduce a novel neural network-based BRDF model and a Bayesian framework for object inverse rendering, i.e., joint estimation of reflectance and natural illumination from a single image of an object of known geometry. The…
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Keywords:
brdf;
invertible neural;
inverse rendering;
model ... See more keywords
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Published in 2023 at "Polymers"
DOI: 10.3390/polym15081884
Abstract: Additive manufacturing has revolutionized prototyping and small-scale production in the past years. By creating parts layer by layer, a tool-less production technology is established, which allows for rapid adaption of the manufacturing process and customization…
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Keywords:
neural networks;
fused deposition;
invertible neural;
process ... See more keywords