◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Sabrina Pechmann

5 papers hereh-index 585 citations13 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • eess.IV3
  • cs.CV2
same name
  • Sabrina Pechmann — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedUltra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography

30 citations · 34 across the 5 of their papers we have counts for

collaborators
Showing eess.IVShow all

3 papers · 1 filter

eess.IV2022

Noise2Contrast: Multi-Contrast Fusion Enables Self-Supervised Tomographic Image Denoising

Fabian Wagner, Mareike Thies, Laura Pfaff +10

Self-supervised image denoising techniques emerged as convenient methods that allow training denoising models without requiring ground-truth noise-free data. Existing methods usual…

eess.IV2022★ 4 cited

On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting

Fabian Wagner, Mareike Thies, Laura Pfaff +9

Computed tomography (CT) is routinely used for three-dimensional non-invasive imaging. Numerous data-driven image denoising algorithms were proposed to restore image quality in low…

eess.IV2022★ 30 cited

Ultra Low-Parameter Denoising: Trainable Bilateral Filter Layers in Computed Tomography

Fabian Wagner, Mareike Thies, Mingxuan Gu +9

Computed tomography is widely used as an imaging tool to visualize three-dimensional structures with expressive bone-soft tissue contrast. However, CT resolution and radiation dose…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.