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T. Khan

4 papers hereh-index 7196 citations21 works total

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
  • cs.CV2
  • eess.IV2
same name
  • T. Khan — 4 papers, h 4
  • T. Khan — 2 papers, h 8
  • T. Khan — 2 papers, h 2
  • T. Khan — 1 paper, h 0
  • T. Khan — 1 paper, h 30
  • T. Khan — 1 paper, h 1

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

activity
20242026
collaborators

4 papers

cs.CV2026

Focal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentation

Moin Safdar, Shahzaib Iqbal, Mubeen Ghafoor +4

Medical image segmentation is essential for clinical applications such as disease diagnosis, treatment planning, and disease development monitoring because it provides precise morp…

cs.CV2025

LFRA-Net: A Lightweight Focal and Region-Aware Attention Network for Retinal Vessel Segmentatio

Mehwish Mehmood, Shahzaib Iqbal, Tariq Mahmood Khan +2

Retinal vessel segmentation is critical for the early diagnosis of vision-threatening and systemic diseases, especially in real-world clinical settings with limited computational r…

eess.IV2024

LVS-Net: A Lightweight Vessels Segmentation Network for Retinal Image Analysis

Mehwish Mehmood, Shahzaib Iqbal, Tariq Mahmood Khan +2

The analysis of retinal images for the diagnosis of various diseases is one of the emerging areas of research. Recently, the research direction has been inclined towards investigat…

eess.IV2024

TAFM-Net: A Novel Approach to Skin Lesion Segmentation Using Transformer Attention and Focal Modulation

Tariq M Khan, Dawn Lin, Shahzaib Iqbal +1

Incorporating modern computer vision techniques into clinical protocols shows promise in improving skin lesion segmentation. The U-Net architecture has been a key model in this are…

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