A5085620627- Electrical and Bioimpedance Tomography
- Non-Destructive Testing Techniques
- Machine Learning and ELM
- Innovation Diffusion and Forecasting
- Face and Expression Recognition
- Consumer Retail Behavior Studies
- Ultrasonics and Acoustic Wave Propagation
- Advanced Algorithms and Applications
- Machine Learning and Algorithms
- Advanced Bandit Algorithms Research
- Online Learning and Analytics
- Infrastructure Maintenance and Monitoring
Civil Aviation University of China
2023
University of Macau
2017
Broad Learning System [1] proposed recently demonstrates efficient and effective learning capability. This model is also proved to be suitable for incremental algorithms by taking the advantages of random vector flat neural networks. In this paper, a modified BLS structure based on K-means feature extraction developed. Compared with original broad system, acceptable performance more complicated data set, such as CIFAR-10, achieved. Furthermore, it that in flexible potential various applications.
Electrical Impedance Tomography (EIT) has become a new inspection tool for damage detection in Carbon Fiber Reinforced Polymer (CFRP) composites. However, the inverse problem of EIT is severely non-linear, ill-posed, and underdetermined, limiting resolution accuracy images reconstructed with EIT. To solve above problems, PCA-Res2Net algorithm CFRP based on Res2Net structure presented, which consists three modules: initial imaging, data dimension reduction deep feature extraction. Firstly, L1...
Abstract Carbon fiber reinforced polymer (CFRP) is electrically conductive, making it possible to detect structural damage of CFRP laminates with electrical impedance tomography (EIT). However, the inverse problem EIT severely non-linear, ill-posed, and underdetermined, thus limiting resolution accuracy images reconstructed EIT. This paper solves based on invertible neural networks (INN) optimizes INN Adamax gradient descent algorithm. Simulation experimental results demonstrated that,...