Results 51 to 60 of about 2,777 (169)
Health Science Reports, Volume 8, Issue 8, August 2025.ABSTRACT Background and Aims Accurate classification of brain tumors is vital for effective treatment planning. Manual assessment of magnetic resonance imaging (MRI) scans is often subjective and time‐consuming. This exploratory study proposes a machine learning approach integrating radiomic features from contrast‐enhanced T1‐weighted MRI scans to ...
Mostafa Jafari +6 more
wiley +1 more source
Deep Convolutional Neural Networks Based on Semi-Discrete Frames
, 2015 Deep convolutional neural networks have led to breakthrough results in practical feature extraction applications. The mathematical analysis of these networks was pioneered by Mallat, 2012.
Bölcskei, Helmut, Wiatowski, Thomas
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Enhanced Hardrock Seismic Imaging Through Multi‐Scale Information‐Guided Unsupervised Learning
Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 2, June 2025.Abstract In hardrock or crystalline rock geological settings, due to low impedance contrast, reflected energy is usually weak. In addition, often stronger surface waves and noncoherent noise are observed including high‐frequency scattering noise, which seriously covers the useful reflection signal. Therefore, imaging of hardrock seismic data with a low
Liuqing Yang +2 more
wiley +1 more source
Multivariate $\alpha$-molecules
, 2016 The suboptimal performance of wavelets with regard to the approximation of multivariate data gave rise to new representation systems, specifically designed for data with anisotropic features.
Flinth, Axel, Schäfer, Martin
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Journal of Geophysical Research: Solid Earth, Volume 130, Issue 4, April 2025.Abstract The Fujairah basin in the Gulf of Oman experienced a complex tectonic evolution related to Late Cretaceous ophiolite obduction and Oligocene‐Miocene Zagros continental collision. The structure of the foreland basin in Oman‐UAE is well‐known, but the structure and evolution of the hinterland basin behind the obducted ophiolite and underlying ...
M. Y. Ali +5 more
wiley +1 more source
Data-Proximal Complementary ℓ1-TV Reconstruction for Limited Data Computed Tomography
MathematicsIn a number of tomographic applications, data cannot be fully acquired, resulting in severely underdetermined image reconstruction. Conventional methods in such cases lead to reconstructions with significant artifacts.
Simon Göppel +2 more
doaj +1 more source
Image Decomposition and Separation Using Sparse Representations: An Overview [PDF]
, 2010 This paper gives essential insights into the use of sparsity and morphological diversity in image decomposition and source separation by reviewing our recent work in this field.
Bobin, Jérôme +3 more
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Advanced Materials, Volume 37, Issue 12, March 26, 2025.We leverage the intrinsic optical anisotropy of the Morpho butterfly wing to introduce Morpho‐Enhanced Polarized Light Microscopy (MorE‐PoL), a stain‐ and contact‐free imaging methodology that quantitatively assesses the microstructural properties of fibrous biological tissues.
Paula Kirya +3 more
wiley +1 more source
, 2003 Energized by the success of wavelets, the last two decades saw the rapid development of a new field, computational harmonic analysis, which aims to develop new systems for effectively representing phenomena of scientific interest.
Candès, Emmanuel J.
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Active Seismic Exploration of Planetary Subsurfaces via Compressive Sensing
Earth and Space Science, Volume 12, Issue 3, March 2025.Abstract Geophysical measurements, such as seismic experiments, are a key target for scientific activities on planetary surfaces. Dense spatial sampling of such measurements is often desirable, and acquisition is traditionally performed at regular intervals.
Jingchuan Wang +16 more
wiley +1 more source