Performance Analysis of Subsea Pipeline Defect Classification Using Supervised Machine Learning
Author:
Affiliation:
1. PES University,Department of Electronics and Communication Engineering,Bengaluru,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10458705/10458718/10458750.pdf?arnumber=10458750
Reference27 articles.
1. 2020/1022: How Digital Tools and Solutions can Improve Subsea Integrity Management;Ellingsen;DNV,2020
2. Detection crack in image using Otsu method and multiple filtering in image processing techniques
3. A robust automatic crack detection method from noisy concrete surfaces
4. Vision-Based Pipe Monitoring Robot for Crack Detection Using Canny Edge Detection Method as an Image Processing Technique
5. Development of Underwater Pipe Crack Detection System for Low-Cost Underwater Vehicle using Raspberry Pi and Canny Edge Detection Method;Aliff,2022
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