Improving Oil Pipeline Surveillance with a Novel 3D Drone Simulation Using Dynamically Constrained Accumulative Membership Fuzzy Logic Algorithm (DCAMFL) for Crack Detection
Abstract Cracks in oil pipelines pose significant risks to the environment, public safety, and the overall integrity of the infrastructure. In this paper, we propose a novel approach for crack detection in oil pipes using a combination of 3D drone simulation, convolutional neural network (CNN) featu...
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| Main Authors: | Omar Saber Muhi, Hameed Mutlag Farhan, Sefer Kurnaz |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | International Journal of Computational Intelligence Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44196-025-00818-3 |
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