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Mayug Maniparambil

18 papers hereh-index 6241 citations20 works total

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

author position
  • first author6
  • middle author12

Across the 18 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CV12
  • eess.IV3
  • astro-ph.IM1
  • cs.AI1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedPhase retrieval for Fourier Ptychography under varying amount of measurements

24 citations · 39 across the 17 of their papers we have counts for

collaborators
Showing eess.IVShow all

3 papers · 1 filter

eess.IV2026

Are Natural-Domain Foundation Models Effective for Accelerated Cardiac MRI Reconstruction?

Anam Hashmi, Mayug Maniparambil, Julia Dietlmeier +2

The emergence of large-scale pretrained foundation models has transformed computer vision, enabling strong performance across diverse downstream tasks. However, their potential for…

eess.IV2023★ 2 cited

The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data

Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle +35

Challenges drive the state-of-the-art of automated medical image analysis. The quantity of public training data that they provide can limit the performance of their solutions. Publ…

eess.IV2023★ 2 cited

An Ensemble Deep Learning Approach for COVID-19 Severity Prediction Using Chest CT Scans

Sidra Aleem, Mayug Maniparambil, Suzanne Little +2

Chest X-rays have been widely used for COVID-19 screening; however, 3D computed tomography (CT) is a more effective modality. We present our findings on COVID-19 severity predictio…

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