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20202025
most citedWhat Makes Transfer Learning Work For Medical Images: Feature Reuse & Other Factors

9 citations · 12 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025

APLA: A Simple Adaptation Method for Vision Transformers

Moein Sorkhei, Emir Konuk, Kevin Smith +1

Existing adaptation techniques typically require architectural modifications or added parameters, leading to high computational costs and complexity. We introduce Attention Project…

cs.CV2025

Efficient Self-Supervised Adaptation for Medical Image Analysis

Moein Sorkhei, Emir Konuk, Jingyu Guo +3

Self-supervised adaptation (SSA) improves foundation model transfer to medical domains but is computationally prohibitive. Although parameter efficient fine-tuning methods such as…

cs.CV2024

Learning from Offline Foundation Features with Tensor Augmentations

Emir Konuk, Christos Matsoukas, Moein Sorkhei +2

We introduce Learning from Offline Foundation Features with Tensor Augmentations (LOFF-TA), an efficient training scheme designed to harness the capabilities of foundation models i…

cs.CV2021★ 3 cited

CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of Cancer

Moein Sorkhei, Yue Liu, Hossein Azizpour +6

Interval and large invasive breast cancers, which are associated with worse prognosis than other cancers, are usually detected at a late stage due to false negative assessments of…

cs.CV2020

Full-Glow: Fully conditional Glow for more realistic image generation

Moein Sorkhei, Gustav Eje Henter, Hedvig Kjellström

Autonomous agents, such as driverless cars, require large amounts of labeled visual data for their training. A viable approach for acquiring such data is training a generative mode…