Results 81 to 90 of about 566 (171)
An adaptive neuro‐fuzzy inference system is presented based on an optimization of genetic algorithm to classify normal and abnormal brain tumours. Abstract An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours.
Marzieh Ghahramani, Nabiollah Shiri
wiley +1 more source
Various regularization terms have been proposed for inverse problems. In this work, we investigate the shearlet-based regularization in the context of sparse-view X-ray computed tomography(XCT) reconstruction of industrial parts.
Xiaoya Chen +3 more
doaj +1 more source
Construction of Meyer Wavelet Using Fully Smooth Sigmiod Function
In order to obtain better smooth effect in signal or image reconstruction, the regularity or continuous differentiability of wavelet must be increased as much as possible.
SHAO Yun-hong, DENG Cai-xia, HE Peng
doaj +1 more source
An Infrared and Visible Image Fusion Algorithm Based on LSWT-NSST
Regarding the problems of image distortion, edge blurring, Gibbs phenomena in the traditional wavelet transform algorithm and the loss of subtle features in the Non-Subsampled Shearlet Transform (NSST), and considering the physical characteristics of ...
Li Junwu, Binhua Li, Yaoxi Jiang
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Deep learning‐based methods for detecting defects in cast iron parts and surfaces
First, this article used multiple data augmentation methods to alleviate the problem of small sample size in casting datasets. Second, attention mechanism was introduced. Finally, a novel feature fusion layer structure was adopted to improve the original network model.
Pengyu Wang, Peng Jing
wiley +1 more source
Asymptotic Analysis of Shearlet Transfom for Inpainting
Supply of missing data, also known as inpainting, is an important application of image processing.Wavelets are commonly used for inpainting algorithms. Shearlet transform which is an affinetransformation is the improvement of the wavelet transform.
Süleyman Çetinkaya +2 more
doaj +1 more source
mBCCf: Multilevel Breast Cancer Classification Framework Using Radiomic Features
Breast cancer characterization remains a significant and challenging issue in contemporary medicine. Accurately distinguishing between malignant and benign breast lesions is crucial for effective diagnosis and treatment. The anatomical structure of malignant breast ultrasound images is more chaotic than that of benign images due to disease pathologies.
Lipismita Panigrahi +6 more
wiley +1 more source
To solve the problems of noise coverage defect and low contrast between the defect and the background of ZrO2 ceramic bearing balls, a surface defect extraction algorithm based on shearlet transform image enhancement for ZrO2 ceramic bearing balls is ...
Dahai Liao +5 more
doaj +1 more source
Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems
In seismic data processing, data recovery including reconstruction of the missing trace and removal of noise from the recorded data are the key steps in improving the signal‐to‐noise ratio (SNR). The reconstruction of seismic data and removal of noise becomes a sparse optimization problem that can be solved by using sparse regularization.
Diriba Gemechu, Francisco Rossomando
wiley +1 more source
A new feature extraction technique called DNST-GLCM-KSR (discrete non-separable shearlet transform-gray-level co-occurrence matrix-kernel spectral regression) is presented according to the direction and texture information of surface defects of ...
Xiaoming Liu +3 more
doaj +1 more source

