15 citations · 17 across the 9 of their papers we have counts for
9 papers
Consensus-gated Multi-Agent Neural Architecture Search for Seismic Fault Segmentation
Shehram Baig, Ahmad Mustafa
Neural networks for seismic fault segmentation are often borrowed from computer vision and medical imaging domains where they train under relatively much larger labeled data resour…
ReCoGNet: Recurrent Context-Guided Network for 3D MRI Prostate Segmentation
Ahmad Mustafa, Reza Rastegar, Ghassan AlRegib
Prostate gland segmentation from T2-weighted MRI is a critical yet challenging task in clinical prostate cancer assessment. While deep learning-based methods have significantly adv…
Man-recon: manifold learning for reconstruction with deep autoencoder for smart seismic interpretation
Ahmad Mustafa, Ghassan AlRegib
Deep learning can extract rich data representations if provided sufficient quantities of labeled training data. For many tasks however, annotating data has significant costs in ter…
Explainable Machine Learning for Hydrocarbon Prospect Risking
Ahmad Mustafa, Ghassan AlRegib
Hydrocarbon prospect risking is a critical application in geophysics predicting well outcomes from a variety of data including geological, geophysical, and other information modali…
Patient Aware Active Learning for Fine-Grained OCT Classification
Yash-yee Logan, Ryan Benkert, Ahmad Mustafa +2
This paper considers making active learning more sensible from a medical perspective. In practice, a disease manifests itself in different forms across patient cohorts. Existing fr…
Joint Learning for Spatial Context-based Seismic Inversion of Multiple Datasets for Improved Generalizability and Robustness
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
Seismic inversion plays a very useful role in detailed stratigraphic interpretation of seismic data. Seismic inversion enables estimation of rock properties over the complete seism…
Joint Learning for Seismic Inversion: An Acoustic Impedance Estimation Case Study
Ahmad Mustafa, Ghassan AlRegib
Seismic inversion helps geophysicists build accurate reservoir models for exploration and production purposes. Deep learning-based seismic inversion works by training a neural netw…
Spatiotemporal Modeling of Seismic Images for Acoustic Impedance Estimation
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
Seismic inversion refers to the process of estimating reservoir rock properties from seismic reflection data. Conventional and machine learning-based inversion workflows usually wo…
Estimation of Acoustic Impedance from Seismic Data using Temporal Convolutional Network
Ahmad Mustafa, Motaz Alfarraj, Ghassan AlRegib
In exploration seismology, seismic inversion refers to the process of inferring physical properties of the subsurface from seismic data. Knowledge of physical properties can prove…