Ground-penetrating radar (GPR) data processing and visualisation: a free and open-source software package (R language)

Awesome Geophysics is a community-curated resource offering essential tools, datasets, and educational materials for geophysical exploration. It’s designed to empower students, researchers, and professionals to analyze data, model Earth processes, and stay connected with the latest industry trends.

python tool to read and plot Geophysical Survey Systems Incorporated (GSSI) radar data

This repository contains code to train object detection models like FRCNN/YOLO for identifying objects in Ground Penetrating Radar scans. It also contains code to generate fake data using Generative Adversarial Networks(GANs).

minimum working example for a B-scan migration with example data

A cheap GPR prototype has been developed by the workgroup of COST Action TU1208.

An example of how to automate the process of training data generation through gprMax for use in machine learning models.

The code and dataset of paper *Multi-View Fusion and Distillation for Subgrade Distresses Detection based on 3D-GPR*

Python wrapper for RGPR (ground-penetrating radar visualisation & processing)

GPR utilities

Companion code to run along with paper [temp]

This framework is a novel Ground Penetrating Radar image analysis framework developed by NS Lab @ CUK, integrating a denoising auto-encoder and channel-wise attention into the YOLOv12 backbone to achieve robust and accurate underground barrier detection under noisy and complex subsurface conditions.

Collaborative Highway Asset Research: Integrated Sensor-Modeling Application (CHARISMA) is a collaborative platform collaborative analysis and visualization of NDE and other infrastructure data and for the fusion of sensor data with digital twin models.

Research website

Awesome Geophysics is a community-curated resource offering essential tools, datasets, and educational materials for geophysical exploration. It’s designed to empower students, researchers, and professionals to analyze data, model Earth processes, and stay connected with the latest industry trends.

An academic project dedicated to processing and analyzing Ground Penetrating Radar (GPR) data to map underground anomalies in 3D using pure Digital Signal Processing (DSP) techniques.

EN : Water Pipe Leakage Risk Prediction System v0-3 | Industrial-grade GPR system achieving R²=0.9894 accuracy with 1,907x parallel processing efficiency | Complete scalability proven from N=44 to N=6000 datasets. JP : 水道管漏水リスク予測GPRシステム v0-3 | 産業レベル予測精度R²=0.9894、1,907倍並列処理効率化を実現したガウス過程回帰による高精度漏水リスク分析システム | N=44→N=6000完全スケーラビリティ実証済み

Deep learning landmine detection trained on synthetic GPR data. gprMax FDTD simulation, AutoKeras neural architecture search, and evaluation pipeline. BEng thesis — IMechE Best Student Award.

Javascript reader of SEG 2 data

Awesome Geophysics is a community-curated resource offering essential tools, datasets, and educational materials for geophysical exploration. It’s designed to empower students, researchers, and professionals to analyze data, model Earth processes, and stay connected with the latest industry trends.