Search Results for author: Nikita Moriakov

Found 9 papers, 1 papers with code

Subpixel object segmentation using wavelets and multi resolution analysis

no code implementations28 Oct 2021 Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

The effectiveness of the proposed method is demonstrated by delineating boundaries of simply connected domains (organs) in medical images using Debauches wavelets and comparing performance with a U-Net baseline.

Semantic Segmentation

Subpixel object segmentation using wavelets and multiresolution analysis

no code implementations29 Sep 2021 Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen

The effectiveness of the proposed method is demonstrated by delineating boundaries of simply connected domains (organs) in medical images using Debauches wavelets and comparing performance with a U-Net baseline.

Semantic Segmentation

Inferring astrophysical X-ray polarization with deep learning

no code implementations16 May 2020 Nikita Moriakov, Ashwin Samudre, Michela Negro, Fabian Gieseke, Sydney Otten, Luc Hendriks

We investigate the use of deep learning in the context of X-ray polarization detection from astrophysical sources as will be observed by the Imaging X-ray Polarimetry Explorer (IXPE), a future NASA selected space-based mission expected to be operative in 2021.

Kernel of CycleGAN as a principal homogeneous space

no code implementations ICLR 2020 Nikita Moriakov, Jonas Adler, Jonas Teuwen

It is known that the CycleGAN problem might admit multiple solutions, and our goal in this paper is to analyze the space of exact solutions and to give perturbation bounds for approximate solutions.

Image-to-Image Translation Translation

Kernel of CycleGAN as a Principle homogeneous space

no code implementations24 Jan 2020 Nikita Moriakov, Jonas Adler, Jonas Teuwen

It is known that the CycleGAN problem might admit multiple solutions, and our goal in this paper is to analyze the space of exact solutions and to give perturbation bounds for approximate solutions.

Image-to-Image Translation Translation

Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation

no code implementations14 Aug 2018 Joris van Vugt, Elena Marchiori, Ritse Mann, Albert Gubern-Mérida, Nikita Moriakov, Jonas Teuwen

We analyze two transfer learning settings: 1) unsupervised transfer, where Hologic data with soft lesion annotation at pixel level and Siemens unlabelled data are used to annotate images in the latter data; 2) weak supervised transfer, where exam level labels for images from the Siemens mammograph are available.

Domain Adaptation Lesion Detection +1

Deep Learning Framework for Digital Breast Tomosynthesis Reconstruction

no code implementations14 Aug 2018 Nikita Moriakov, Koen Michielsen, Jonas Adler, Ritse Mann, Ioannis Sechopoulos, Jonas Teuwen

In this study we propose an extension of the Learned Primal-Dual algorithm for digital breast tomosynthesis.

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