GitHub / RamySaleem / SeismicStructuralAnalysis-CNN-Object-Detection
Our project revolutionizes seismic image interpretation with advanced deep learning, using Convolutional Neural Networks (CNNs) to automate workflows and improve accuracy in subsurface exploration. Trained on synthetic seismic data from coal mines, our algorithm excels in identifying faults, folds, and flat layers.
Stars: 1
Forks: 0
Open issues: 0
License: gpl-3.0
Language: Jupyter Notebook
Size: 92.2 MB
Dependencies parsed at: Pending
Created at: over 2 years ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago
Topics: automatic-detection, cnn, coalmines, computer-vision, convolutional-neural-networks, deep-learning, detectron2, instance-segmentation, machine-learning, object-detection, seismic-data, seismic-interpretation, seismic-synthetic, synthetic-data, yolov7, yolov8