This repository contains the official open-source code for [YOLO vs. Diffusion Networks for Underground PipeDetection: A Case Study Using Ground PenetratingRadar Data]. ### OverviewThis software provides an end-to-end implementation of deep Learning for Pipeline Detection Using GPR Data . ### Contents* `data/`: Data preprocessing scripts and configuration files.* `models/`: Deep learning architecture definitions and configurations.* `experiments/`: Training routines, cross-validation scripts, and evaluation pipelines.* `README.md`: Detailed setup instructions and dependency requirements. ### Quick StartTo set up the environment and run the main workflow: 1. Install dependencies: `pip install -r requirements.txt`2. Run the main script Please refer to the `README.md` file inside the archive for detailed folder-by-folder usage guidelines. ### CitationIf you use this code in your research, please cite our manuscript/repository as detailed in the citation section.
The importance of power transformers in electrical power systems cannot be overstated, as their failures can lead to considerable economic losses and disruptions. The typical malfunctions encountered by a power transformer comprise dielectric issues, thermal losses due to copper…
Abstract: 5G is rolled out and next generation 6G networks are also being developed, ultra-low latency (URLL) communication as a standard is critical in supporting the plethora of applications, spanning autonomous vehicles, immersive extended reality experience, etc. However, tra…
Explainable AI (XAI) methods such as SHAP are increasingly presented to security operations center (SOC) analysts as a way to justify machine-learning-based network intrusion detection system (NIDS) alerts, on the premise that a stated explanation increases trust and speeds triag…
The increasing reliance on third-party packages from repositories such as Python Package Index (PyPI) and Node Package Manager (NPM) has introduced critical vulnerabilities in software supply chains. Traditional security approaches, including signature-based detection and trust e…
This repository contains the data used for training and validation of the model presented in Decadal wave reconstruction in the Mediterranean Sea with graph neural networks by Benassi et al. The wave data will be published as Wadalkar et al. (2026), a bias-corrected version of th…
Early detection of disease is a cornerstone for improving patient outcomes, reducing costs, and enabling preventative interventions. Traditional predictive models often rely on a single type of data (e.g., imaging, clinical labs, or genomics). However, human health is inherently…