Searched for: author%3A%22Seifert%2C+Jacob%22
(1 - 3 of 3)
document
Seifert, Jacob (author), Shao, Y. (author), Mosk, Allard P. (author)
Computational imaging is increasingly vital for a broad spectrum of applications, ranging from biological to material sciences. This includes applications where the object is known and sufficiently sparse, allowing it to be described with a reduced number of parameters. When no explicit parameterization is available, a deep generative model...
journal article 2024
document
Seifert, Jacob (author), Shao, Y. (author), van Dam, Rens (author), Bouchet, Dorian (author), van Leeuwen, Tristan (author), Mosk, Allard P. (author)
Optical measurements often exhibit mixed Poisson–Gaussian noise statistics, which hampers the image quality, particularly under low signal-to-noise ratio (SNR) conditions. Computational imaging falls short in such situations when solely Poissonian noise statistics are assumed. In response to this challenge, we define a loss function that...
journal article 2023
document
Weerdenburg, S. (author), Shao, Y. (author), Seifert, Jacob (author), Horsten, R.C. (author), Coene, W.M.J.M. (author)
We demonstrate our beamline using a table-top HHG EUV source for lensless imaging application in reflection m ode. T he s ample r eflection fu nction is reconstructed using an auto-differentiation based ptychographic algorithm built on TensorFlow platform.
conference paper 2022