Correlated-Weighted Statistically Modeled Contourlet and Curvelet Coefficient Image-Based Breast Tumor Classification Using Deep Learning [PDF]
Diagnostics, 2022 Deep learning-based automatic classification of breast tumors using parametric imaging techniques from ultrasound (US) B-mode images is still an exciting research area.
Shahriar M. Kabir +1 more
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Compactly Supported Curvelet-Type Systems [PDF]
Journal of Function Spaces and Applications, 2012 We study a flexible method for constructing curvelet-type frames. These curvelet-type systems have the same sparse representation properties as curvelets for appropriate classes of smooth functions, and the flexibility of the method allows us to give a ...
Kenneth N. Rasmussen, Morten Nielsen
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A Hybrid Method to Enhance Thick and Thin Vessels for Blood Vessel Segmentation [PDF]
Diagnostics, 2021 Retinal blood vessels have been presented to contribute confirmation with regard to tortuosity, branching angles, or change in diameter as a result of ophthalmic disease.
Sonali Dash +6 more
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Curvelet transform for Boehmians
Arab Journal of Mathematical Sciences, 2014 By proving the required auxiliary results, two Boehmian spaces are constructed for the purpose of extending the curvelet transform to the context of Boehmian spaces. A convolution theorem for curvelet transform is proved.
Subash Moorthy Rajendran +1 more
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Curvelet-enhanced transformer architecture for blurred action fine-grained detection [PDF]
Scientific ReportsThis study proposes a novel Multi Curvelet Transformer Network (MCTN) for fine-grained human behavior recognition in dynamic video scenarios. A key challenge in this field lies in accurately identifying human actions under adverse conditions such as ...
Yuxiang Ren +4 more
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AEJ - Alexandria Engineering Journal, 2020 To ensure safety of maintenance of refinery unit and improve reliability of refinery unit, the risk assessment model of refinery unit maintenance is established based on fuzzy second generation curvelet neural network optimized by improved firefly ...
Bin Zhao +3 more
exaly +3 more sources
Evaluating machine learning models for post-surgery treatment response assessment in glioblastoma multiforme: a comparative study of gray level co-occurrence matrix (GLCM), curvelet, and combined radiomics features selected by multiple algorithms [PDF]
BMC Medical ImagingBackground Developing quantitative methods to assess post-surgery treatment response in Glioblastoma Multiforme (GBM) is critical for improving patient outcomes and refining current subjective approaches.
Sanaz Alibabaei +4 more
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The curvelet transform for image denoising [PDF]
IEEE Transactions on Image Processing, 2002 We describe approximate digital implementations of two new mathematical transforms, namely, the ridgelet transform and the curvelet transform. Our implementations offer exact reconstruction, stability against perturbations, ease of implementation, and low computational complexity.
Jean-Luc Starck
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Low light image enhancement using curvelet transform and iterative back projection [PDF]
Scientific Reports, 2023 With the advancement of technology in image capturing, people are accustomed to high-resolution images. One of the primary necessities of an image capturing system is to provide the same.
Sreekala Kannoth +2 more
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Fast Discrete Curvelet Transforms [PDF]
Multiscale Modeling and Simulation, 2006 This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions. The first digital transformation is based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected Fourier samples.
Emmanuel Candes +2 more
exaly +3 more sources