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Internal-Pipe-Corrosion-Assessment-with-Ultrasound-and-CNNs

imported

software/internal-pipe-corrosion-assessment-with-ultrasound-and-cnns

This study introduces a dual-mode methodology for quantifying pipe corrosion by employing ultrasound technology in conjunction with convolutional neural networks (CNN).

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Documentation
unknown
Tags
convolutional-neural-networks · ultrasonic-sensor · ultrasound
Regulatory
unknown
built by · 2

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

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Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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sources
  1. api.github.com/repos/NSLab-CUK/Internal-Pipe-Corrosion-Assessment-with-Ultrasound-and-CNNs
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2025-07-23, 7 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/43.json→ .entries["internal-pipe-corrosion-assessment-with-ultrasound-and-cnns"]

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