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Mohamed Abdur Rahman

3 papers hereh-index 338 citations8 works total

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

author position
  • first author1
  • middle author1

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • eess.IV1
same name
  • Mohamed Abdur Rahman — 2 papers, h 2
  • Mohamed Abdur Rahman — 1 paper, h 15
  • Mohamed Abdur Rahman — 1 paper, h 5
  • Mohamed Abdur Rahman — 1 paper, h 3

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 citedHANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging

3 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CV2025

ReFRM3D: A Radiomics-enhanced Fused Residual Multiparametric 3D Network with Multi-Scale Feature Fusion for Glioma Characterization

Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Md Noman Hossain +4

Gliomas are among the most aggressive cancers, with complex diagnostic processes. Existing glioma segmentation methods often struggle with high variability in imaging data and inad…

cs.CV2025★ 1 cited

A fine-grained attention and geometric correspondence model for musculoskeletal risk classification in athletes using multimodal visual and skeletal features

Md. Abdur Rahman, Mohaimenul Azam Khan Raiaan, Tamanna Shermin +3

Musculoskeletal disorders pose significant risks to athletes, and early risk assessment is essential for prevention. However, most existing methods are designed for controlled sett…

eess.IV2025★ 3 cited

HANS-Net: Hyperbolic Convolution and Adaptive Temporal Attention for Accurate and Generalizable Liver and Tumor Segmentation in CT Imaging

Arefin Ittesafun Abian, Ripon Kumar Debnath, Md. Abdur Rahman +5

Accurate liver and tumor segmentation on abdominal CT images is critical for reliable diagnosis and treatment planning, but remains challenging due to complex anatomical structures…

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