In this paper, we propose a novel wind-speed forecasting model that combines the stationary wavelet transform with quaternion-valued neural networks.
Annotating seismic data is expensive, laborious and subjective due to the number of years required for seismic interpreters to attain proficiency in interpretation.
It is our hope that this comparative study will help acquaint the seismic interpretation community with the many available powerful image texture analysis techniques, providing more alternative attributes for their seismic exploration.
no code implementations • 19 Dec 2018 • Zhiling Long, Yazeed Alaudah, Muhammad Ali Qureshi, Yuting Hu, Zhen Wang, Motaz Alfarraj, Ghassan AlRegib, Asjad Amin, Mohamed Deriche, Suhail Al-Dharrab, Haibin Di
We focus on spatial attributes in this study and examine them in a new application for seismic interpretation, i. e., seismic volume labeling.