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Fuad M. Noman

School of Information Technology, Monash University Malaysia

4 papers hereh-index 12629 citations44 works total

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

author position
  • middle author3

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

fields
  • cs.LG2
  • cs.CV1
  • q-bio.NC1
affiliations
  • School of Information Technology, Monash University Malaysia
ORCID 0000-0002-1756-8239

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

q-bio.NC2025

Brain-MGF: Multimodal Graph Fusion Network for EEG-fMRI Brain Connectivity Analysis Under Psilocybin

Sin-Yee Yap, Fuad Noman, Junn Yong Loo +6

Psychedelics, such as psilocybin, reorganise large-scale brain connectivity, yet how these changes are reflected across electrophysiological (electroencephalogram, EEG) and haemody…

cs.LG2025

T2I-Diff: fMRI Signal Generation via Time-Frequency Image Transform and Classifier-Free Denoising Diffusion Models

Hwa Hui Tew, Junn Yong Loo, Yee-Fan Tan +5

Functional Magnetic Resonance Imaging (fMRI) is an advanced neuroimaging method that enables in-depth analysis of brain activity by measuring dynamic changes in the blood oxygenati…

cs.CV2025

SFC-GAN: A Generative Adversarial Network for Brain Functional and Structural Connectome Translation

Yee-Fan Tan, Jun Lin Liow, Pei-Sze Tan +4

Modern brain imaging technologies have enabled the detailed reconstruction of human brain connectomes, capturing structural connectivity (SC) from diffusion MRI and functional conn…

cs.LG2024

A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identification

Sin-Yee Yap, Junn Yong Loo, Chee-Ming Ting +4

Recent applications of pattern recognition techniques on brain connectome classification using functional connectivity (FC) are shifting towards acknowledging the non-Euclidean top…

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