A Novel Cascaded Deep Learning Model for the Detection and Quantification of Defects in Pipelines via Magnetic Flux Leakage Signals-Reference-Cited by-同舟云学术

A Novel Cascaded Deep Learning Model for the Detection and Quantification of Defects in Pipelines via Magnetic Flux Leakage Signals

Author:

Yuksel Veysel¹^ORCID,Tetik Yusuf Engin¹^ORCID,Basturk Mahmut Omer²^ORCID,Recepoglu Onur¹^ORCID,Gokce Kursad¹^ORCID,Cimen Mehmet Ali³^ORCID

Affiliation:

1. Department of Robotics and Smart Systems, Rail Transport Technologies Institute (RUTE), Kocaeli, Turkey

2. Department of Computer Engineering and the Faculty of Computer and Informatics Engineering, İstanbul Technical University, İstanbul, Turkey

3. Rail Transport Technologies Institute (RUTE), Kocaeli, Turkey

Funder

IGDAS (Istanbul, Turkey), a gas distribution company through the Pipeline Inspection Robot for 12”-16” Natural Gas Distribution Pipelines Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

Reference44 articles.

2. Distance-IoU loss: Faster and better learning for bounding box regression;zheng;arXiv 1911 08287,2019

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