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researcher

M. Saad

8 papers hereh-index 5163 citations13 works total

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

author position
  • first author6
  • middle author2

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • eess.IV5
  • cs.CV1
  • cs.CY1
  • cs.LG1
same name
  • M. Saad — 10 papers, h 5
  • M. Saad — 5 papers, h 3
  • M. Saad — 3 papers, h 7
  • M. Saad — 2 papers, h 9
  • M. Saad — 2 papers, h 11
  • M. Saad — 2 papers, 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
20222024
most citedA Survey on Training Challenges in Generative Adversarial Networks for Biomedical Image Analysis

7 citations · 12 across the 8 of their papers we have counts for

collaborators
Showing 2022 · eess.IVShow all

3 papers · 2 filters

eess.IV2022

A Self-attention Guided Multi-scale Gradient GAN for Diversified X-ray Image Synthesis

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

Imbalanced image datasets are commonly available in the domain of biomedical image analysis. Biomedical images contain diversified features that are significant in predicting targe…

eess.IV2022

Evaluating the Quality and Diversity of DCGAN-based Generatively Synthesized Diabetic Retinopathy Imagery

Cristina-Madalina Dragan, Muhammad Muneeb Saad, Mubashir Husain Rehmani +1

Publicly available diabetic retinopathy (DR) datasets are imbalanced, containing limited numbers of images with DR. This imbalance contributes to overfitting when training machine…

eess.IV2022

Addressing the Intra-class Mode Collapse Problem using Adaptive Input Image Normalization in GAN-based X-ray Images

Muhammad Muneeb Saad, Mubashir Husain Rehmani, Ruairi O'Reilly

Biomedical image datasets can be imbalanced due to the rarity of targeted diseases. Generative Adversarial Networks play a key role in addressing this imbalance by enabling the gen…

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