74 citations · 248 across the 25 of their papers we have counts for
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Self-Supervised Annotation of Seismic Images using Latent Space Factorization
Oluwaseun Joseph Aribido, Ghassan AlRegib, Mohamed Deriche
Annotating seismic data is expensive, laborious and subjective due to the number of years required for seismic interpreters to attain proficiency in interpretation. In this paper,…
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…
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset
Yuting Hu, Zhiling Long, Anirudha Sundaresan +4
Tactile sensing or fabric hand plays a critical role in an individual's decision to buy a certain fabric from the range of available fabrics for a desired application. Therefore, t…
Texture Classification using Block Intensity and Gradient Difference (BIGD) Descriptor
Yuting Hu, Zhen Wang, Ghassan AlRegib
In this paper, we present an efficient and distinctive local descriptor, namely block intensity and gradient difference (BIGD). In an image patch, we randomly sample multi-scale bl…
Semi-supervised Learning for Acoustic Impedance Inversion
Motaz Alfarraj, Ghassan AlRegib
Recent applications of deep learning in the seismic domain have shown great potential in different areas such as inversion and interpretation. Deep learning algorithms, in general,…
Structure Label Prediction Using Similarity-Based Retrieval and Weakly-Supervised Label Mapping
Yazeed Alaudah, Motaz Alfarraj, Ghassan AlRegib
Recently, there has been significant interest in various supervised machine learning techniques that can help reduce the time and effort consumed by manual interpretation workflows…
Multiscale Fusion for Seismic Geometric Attribute Enhancement
Motaz Alfarraj, Haibin Di, Ghassan AlRegib
In this abstract, we propose a multiscale fusion technique to enhance seismic geometric attributes, such as dip and curvature, which are very sensitive to noise present in seismic…
Multiresolution Analysis and Learning for Computational Seismic Interpretation
Motaz Alfarraj, Yazeed Alaudah, Zhiling Long +1
We explore the use of multiresolution analysis techniques as texture attributes for seismic image characterization, especially in representing subsurface structures in large migrat…
Noise-robust detection and tracking of salt domes in postmigrated volumes using texture, tensors, and subspace learning
Zhen Wang, Tamir Hegazy, Zhiling Long +1
The identification of salt dome boundaries in migrated seismic data volumes is important for locating petroleum reservoirs. The presence of noise in the data makes computer-aided s…
A High-Speed, Real-Time Vision System for Texture Tracking and Thread Counting
Yuting Hu, Zhiling Long, Ghassan AlRegib
In garment manufacturing, an automatic sewing machine is desirable to reduce cost. To accomplish this, a high speed vision system is required to track fabric motions and recognize…