Results 61 to 70 of about 1,112 (156)
IET Image Processing, Volume 18, Issue 5, Page 1358-1372, 17 April 2024.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
Deep learning‐based methods for detecting defects in cast iron parts and surfaces
IET Image Processing, Volume 18, Issue 1, Page 47-58, 10 January 2024.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
Democracy of shearlet frames with applications
Journal of Approximation Theory, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Computerized tomography with total variation and with shearlets [PDF]
Inverse Problems, 2017 To reduce the x-ray dose in computerized tomography (CT), many constrained optimization approaches have been proposed aiming at minimizing a regularizing function that measures lack of consistency with some prior knowledge about the object that is being imaged, subject to a (predetermined) level of consistency with the detected attenuation of x-rays ...
Edgar Garduño, Gabor T. Herman
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mBCCf: Multilevel Breast Cancer Classification Framework Using Radiomic Features
International Journal of Intelligent Systems, Volume 2024, Issue 1, 2024.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
Sparse Regularization Based on Orthogonal Tensor Dictionary Learning for Inverse Problems
Mathematical Problems in Engineering, Volume 2024, Issue 1, 2024.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
Bendlet Transform Based Adaptive Denoising Method for Microsection Images. [PDF]
Entropy (Basel), 2022 Mei S +5 more
europepmc +1 more source
Noise reduction by adaptive-SIN filtering for retinal OCT images. [PDF]
Sci Rep, 2021 Hu Y, Ren J, Yang J, Bai R, Liu J.
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Automated Diagnosis and Assessment of Cardiac Structural Alteration in Hypertension Ultrasound Images. [PDF]
Contrast Media Mol Imaging, 2022 Raghavendra U +11 more
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Shearlets and Microlocal Analysis [PDF]
, 2012 Although wavelets are optimal for describing pointwise smoothness properties of univariate functions, they fail to efficiently characterize the subtle geometric phenomena of multidimensional singularities in high-dimensional functions. Mathematically these phenomena can be captured by the notion of the wavefront set which describes point- and direction-
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