Weld defect classification in radiographic images using unified deep neural network with multi-level features
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Weld defect classification in radiographic images using unified deep neural network with multi-level features
Authors
Keywords
-
Journal
JOURNAL OF INTELLIGENT MANUFACTURING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-05-12
DOI
10.1007/s10845-020-01581-2
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Unsupervised weld defect classification in radiographic images using multivariate generalized Gaussian mixture model with exact computation of mean and shape parameters
- (2019) Nafaa Nacereddine et al. COMPUTERS IN INDUSTRY
- Liver disease screening based on densely connected deep neural networks
- (2019) Zhenjie Yao et al. NEURAL NETWORKS
- Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE
- (2018) Xiaofeng Yuan et al. IEEE Transactions on Industrial Informatics
- On the Reconstruction of Face Images from Deep Face Templates
- (2018) Guangcan Mai et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Real-time head pose estimation using multi-task deep neural network
- (2018) Byungtae Ahn et al. ROBOTICS AND AUTONOMOUS SYSTEMS
- Using deep neural network with small dataset to predict material defects
- (2018) Shuo Feng et al. MATERIALS & DESIGN
- Classification of weld defects based on the analytical hierarchy process and Dempster–Shafer evidence theory
- (2017) Hongquan Jiang et al. JOURNAL OF INTELLIGENT MANUFACTURING
- Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
- (2016) Feng Jia et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Weld Defect Detection of X-ray Images Based on Support Vector Machine
- (2014) Yong Wang et al. IETE TECHNICAL REVIEW
- Automatic classification approach to weld defects based on PCA and SVM
- (2013) Weilei Mu et al. INSIGHT
- Automated Defect Recognition and Identification in Digital Radiography
- (2013) P. Baniukiewicz JOURNAL OF NONDESTRUCTIVE EVALUATION
- Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
- (2012) Geoffrey Hinton et al. IEEE SIGNAL PROCESSING MAGAZINE
- Automatic Inspection System of Welding Radiographic Images Based on ANN Under a Regularisation Process
- (2011) Juan Zapata et al. JOURNAL OF NONDESTRUCTIVE EVALUATION
- Automatic classification of weld defects in radiographic images
- (2010) Qingming Shen et al. INSIGHT
- An automatic system of classification of weld defects in radiographic images
- (2009) Rafael Vilar et al. NDT & E INTERNATIONAL
- Improving the accuracy of computer-aided radiographic weld inspection by feature selection
- (2008) T. Warren Liao NDT & E INTERNATIONAL
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started