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Peyman Nejat

4 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cs.CV1
  • cs.IR1
ORCID 0000-0001-9223-7942

identity via Semantic Scholar / OpenAlex

most citedWhen is a Foundation Model a Foundation Model

6 citations · 6 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2024

SPLICE -- Streamlining Digital Pathology Image Processing

Areej Alsaafin, Peyman Nejat, Abubakr Shafique +4

Digital pathology and the integration of artificial intelligence (AI) models have revolutionized histopathology, opening new opportunities. With the increasing availability of Whol…

cs.CV2023

Selection of Distinct Morphologies to Divide & Conquer Gigapixel Pathology Images

Abubakr Shafique, Saghir Alfasly, Areej Alsaafin +3

Whole slide images (WSIs) are massive digital pathology files illustrating intricate tissue structures. Selecting a small, representative subset of patches from each WSI is essenti…

eess.IV2023

Creating an Atlas of Normal Tissue for Pruning WSI Patching Through Anomaly Detection

Peyman Nejat, Areej Alsaafin, Ghazal Alabtah +7

Patching gigapixel whole slide images (WSIs) is an important task in computational pathology. Some methods have been proposed to select a subset of patches as WSI representation fo…

cs.IR2023★ 6 cited

When is a Foundation Model a Foundation Model

Saghir Alfasly, Peyman Nejat, Sobhan Hemati +13

Recently, several studies have reported on the fine-tuning of foundation models for image-text modeling in the field of medicine, utilizing images from online data sources such as…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.