Non-destructive testing (NDT) techniques play a crucial role in industrial production, aerospace, healthcare, and the inspection of special equipment, serving as an indispensable part of assessing the safety condition of pressure equipment. Among these, the analysis of NDT data stands as a critical link in evaluating equipment safety. In recent years, object detection techniques have gradually been applied to the analysis of NDT data in pressure equipment inspection, yielding significant results. This paper comprehensively reviews the current applications and development trends of object detection algorithms in NDT technology for pressure-bearing equipment, focusing on algorithm selection, data augmentation, and intelligent defect recognition based on object detection algorithms. Additionally, it explores open research challenges of integrating GAN-based data augmentation and unsupervised learning to further enhance the intelligent application and performance of object detection technology in NDT for pressure-bearing equipment while discussing techniques and methods to improve the interpretability of deep learning models. Finally, by summarizing current research and offering insights for future directions, this paper aims to provide researchers and engineers with a comprehensive perspective to advance the application and development of object detection technology in NDT for pressure-bearing equipment.
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http://dx.doi.org/10.3390/s24185944 | DOI Listing |
Bioethics
December 2024
Facultad de Derecho, Universidad de León, León, Spain.
Monitoring health is one of the basic principles of Occupational Health and Safety. The main objective of this monitoring will be the detection of possible damage to health arising from work. They try to discover the effects that the inherent risks with the work may cause the worker, which will show, given the case, through an alteration of health or the state of organic and functional state, both physically and mentally.
View Article and Find Full Text PDFMed Image Anal
December 2024
University of Strasbourg, CAMMA, ICube, CNRS, INSERM, France; IHU Strasbourg, Strasbourg, France.
Accurate tool tracking is essential for the success of computer-assisted intervention. Previous efforts often modeled tool trajectories rigidly, overlooking the dynamic nature of surgical procedures, especially tracking scenarios like out-of-body and out-of-camera views. Addressing this limitation, the new CholecTrack20 dataset provides detailed labels that account for multiple tool trajectories in three perspectives: (1) intraoperative, (2) intracorporeal, and (3) visibility, representing the different types of temporal duration of tool tracks.
View Article and Find Full Text PDFAm J Vet Res
December 2024
Global Diagnostics, Zoetis Inc, Parsippany, NJ.
Objective: To perform a diagnostic assessment of a point-of-care veterinary multiuse platform integrated with a model comprised of deep-learning, convolutional neural network algorithms for evaluating canine/feline peripheral blood smears compared to board-certified clinical pathologists (CPs).
Methods: This study had a blinded, randomized, incomplete block design, and results were compared between CPs and algorithms. Blood smears from convenience samples from veterinary diagnostic reference laboratories from October to December 2021 were used.
J Vis
December 2024
School of Psychological Science, University of Bristol, Bristol, UK.
Being able to detect changes in our visual environment reliably and quickly is important for many daily tasks. The motion silencing effect describes a decrease in the ability to detect feature changes for faster moving objects compared with stationary or slowly moving objects. One theory is that spatiotemporal receptive field properties in early vision might account for the silencing effect, suggesting that its origins are low-level visual processing.
View Article and Find Full Text PDFMed Phys
December 2024
Research Center for Advanced Detection Materials and Medical Imaging Devices, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China.
Background: The complementary absorption contrast CT (ACT) and differential phase contrast CT (DPCT) can be generated simultaneously from an x-ray computed tomography (CT) imaging system incorporated with grating interferometer. However, it has been reported that ACT images exhibit better spatial resolution than DPCT images. By far, the primary cause of such discrepancy remains unclear.
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