[HTML][HTML] Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review

W Wang, J Chen, G Han, X Shi, G Qian - Sensors, 2024 - mdpi.com
Non-destructive testing (NDT) techniques play a crucial role in industrial production,
aerospace, healthcare, and the inspection of special equipment, serving as an …

[HTML][HTML] A comprehensive overview of the fabrication and testing methods of FRP composite pipes

SM Kennedy, RBJ Robert, RMR Prince, GS Hikku… - MethodsX, 2024 - Elsevier
The current work offers a comprehensive and in-depth examination of Fiber Reinforced
Composite pipes mainly dealing with Carbon Fiber Reinforced Polymer (CFRP) composite …

Integrating AI in NDE: Techniques, Trends, and Further Directions

E Pérez, CE Ardic, O Çakıroğlu, K Jacob… - arxiv preprint arxiv …, 2024 - arxiv.org
The digital transformation is fundamentally changing our industries, affecting planning,
execution as well as monitoring of production processes in a wide range of application …

[HTML][HTML] Towards enhancing automated defect recognition (ADR) in digital X-ray radiography applications: synthesizing training data through X-ray intensity …

B Hena, Z Wei, L Perron, CI Castanedo, X Maldague - Information, 2023 - mdpi.com
Industrial radiography is a pivotal non-destructive testing (NDT) method that ensures quality
and safety in a wide range of industrial sectors. Conventional human-based approaches …

Automated Damage and Defect Detection with Low-Cost X-ray Radiography Using Data-Driven Predictor Models and Data Augmentation by X-ray Simulation

S Bosse - Engineering Proceedings, 2023 - mdpi.com
The detection of hidden defects in materials using X-ray images is still a challenge. Often, a
lot of defects are not directly visible in visual inspection. In this work, a data-driven feature …

[HTML][HTML] High-quality, low-quantity: A data-centric approach to deep learning performance optimization in digital X-Ray radiography

B Hena, Z Wei, C Ibarra-Castanedo, X Maldague - NDT & E International, 2025 - Elsevier
The accuracy of identifying defects using specialized deep learning models can be affected
by the circumstances in which the training data is curated. This is especially evident in digital …

Defects Prediction Method for Radiographic Images Based on Random PSO Using Regional Fluctuation Sensitivity

Z Shang, B Li, L Chen, L Zhang - Sensors, 2023 - mdpi.com
This paper presents an advanced methodology for defect prediction in radiographic images,
predicated on a refined particle swarm optimization (PSO) algorithm with an emphasis on …

Real-Time Detection of Rice Quantity in Institutional Food Service Using the DeepLabV3Plus Deep Learning Algorithm

YH Park, EY Choi - Culinary Science & Hospitality Research, 2024 - dbpia.co.kr
This study aimed to identify the most suitable algorithm for accurate and efficient real-time
rice quantity detection on white serving trays to enhance personalized nutrition management …

Pruebas de constancia y calidad de la imagen de Radiografía Digital

GH Vera Patiño, MC Ortiz Hernández - repository.unad.edu.co
Este documento es un análisis detallado sobre las pruebas de constancia en la radiografía
digital y su relación con la calidad de la imagen. Se discuten los criterios de calidad de la …

[CITATA][C] 극점 데이터와 One-class SVM 을 활용한 금속 배관 X-ray 영상의 용접부 검출

진성욱, 이정민, 권은, 박긍휼, 서준성… - 대한기계학회 춘추학술 …, 2023 - dbpia.co.kr
This study proposes a method for effectively exploring regions of interest containing welding
defects in X-ray images of welded metal pipes using statistical techniques and machine …