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Leonid Mill

Researcher at University of Erlangen-Nuremberg

Publications -  14
Citations -  354

Leonid Mill is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Iterative reconstruction & Computer science. The author has an hindex of 4, co-authored 12 publications receiving 170 citations. Previous affiliations of Leonid Mill include Max Planck Society.

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Learning with Known Operators reduces Maximum Training Error Bounds.

TL;DR: In this article, an approach for incorporating prior knowledge into machine learning algorithms is described. But this approach is aimed at applications in physics and signal processing in which we know that certain operations must be embedded into the algorithm.
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Next-generation imaging of the skeletal system and its blood supply

TL;DR: Advanced imaging technologies and big data analysis now enable the unprecedented examination of bone and provide new insights into its 3D macrostructure and microstructure, which could provide the basis for early detection and precision-type intervention of bone disorders in the future.
Journal ArticleDOI

Learning with Known Operators reduces Maximum Training Error Bounds

TL;DR: In this article, an approach for incorporating prior knowledge into machine learning algorithms is described. But this approach is aimed at applications in physics and signal processing in which we know that certain operations must be embedded into the algorithm.
Journal ArticleDOI

Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation

TL;DR: This study paves the way towards the use of deep learning for automated, high-throughput particle detection in a variety of imaging techniques such as microscopies and spectroscopies, for a wide variety of studies and applications, including the detection of plastic micro- and nanoparticles.