Weld defect classification in radiographic images using unified deep neural network with multi-level features
نویسندگان
چکیده
منابع مشابه
Multiclass defect detection and classification in weld radiographic images using geometric and texture features
In this paper, a method for the detection and classification of defects in weld radiographs is presented. The method has been applied for detecting and discriminating discontinuities in the weld images that may correspond to false alarms or defects such as worm holes, porosity, linear slag inclusion, gas pores, lack of fusion or crack. A set of 43 descriptors corresponding to texture measuremen...
متن کاملWeld Classification In Radiographic Images : Data Mining Approach
The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded structures such as pressure vessels, load bearing structural members and power plants has long been recognized. This paper presents an application of data mining approach for weld data extracted from reported radiographic images. Data mining is the extraction of implicit, previously unknown and potentia...
متن کاملTextile Defect Classification Using Neural Network
The global market for textile industry is highly competitive nowadays. Quality control in production process in textile industry has been a key factor for retaining existence in such competitive market. Automated textile inspection systems are very useful in this respect, because manual inspection is time consuming and not accurate enough. Hence, automated textile inspection systems have been d...
متن کاملImage Thresholding for Weld Defect Extraction in Industrial Radiographic Testing
In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must...
متن کاملSegmentation of the Left Atrial Appendage in the Echocardiographic Images of the Heart Using a Deep Neural Network
Introduction: Cardiovascular diseases are one of the leading causes of mortality in today’s industrial world. Occlusion of left atrial appendage (LAA) using the manufactured devices is a growing trend. The objective of this study was to develop a computer-aided diagnosis system for the identification of LAA in echocardiographic images. Method: The data used in this descriptive analytical study ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Intelligent Manufacturing
سال: 2020
ISSN: 0956-5515,1572-8145
DOI: 10.1007/s10845-020-01581-2