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Ivan Volaric and Victor Sucic
One of the frequently used classes of sparse reconstruction algorithms is based on the iterative shrinkage/thresholding procedure, in which the thresholding parameter controls a trade-off between the algorithm?s accuracy and execution time. In order to a...
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Shengqin Bian, Xinyu He, Zhengguang Xu and Lixin Zhang
Noise filtering is a crucial task in digital image processing, performing the function of preprocessing. In this paper, we propose an algorithm that employs deep convolution and soft thresholding iterative algorithms to extract and learn the features of ...
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Peilu Li, Chunguang Xu, Qinxue Pan, Yuren Lu and Shuangyi Li
According to the acousto elastic effect, the residual stress on the surface of the rail can be evaluated by measuring the change in the propagation velocity of ultrasonic waves, such as longitudinal critically refracted (LCR) waves on the surface of the ...
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Dilovan Asaad Zebari, Dheyaa Ahmed Ibrahim, Diyar Qader Zeebaree, Mazin Abed Mohammed, Habibollah Haron, Nechirvan Asaad Zebari, Robertas Dama?evicius and Rytis Maskeliunas
Breast cancer detection using mammogram images at an early stage is an important step in disease diagnostics. We propose a new method for the classification of benign or malignant breast cancer from mammogram images. Hybrid thresholding and the machine l...
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Xiang Li, Linlu Dong, Biao Li, Yifan Lei and Nuwen Xu
Microseismic signal denoising is of great significance for P wave, S wave first arrival picking, source localization, and focal mechanism inversion. Therefore, an Empirical Mode Decomposition (EMD), Compressed Sensing (CS), and Soft-thresholding (ST) com...
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