Results 1 to 10 of about 278 (146)
Normalized group activations based feature extraction technique using heterogeneous data for Alzheimer’s disease classification [PDF]
PeerJ Computer ScienceSeveral deep learning networks are developed to identify the complex atrophic patterns of Alzheimer's disease (AD). Among various activation functions used in deep neural networks, the rectifier linear unit is the most used one.
Krishnakumar Vaithianathan +5 more
doaj +3 more sources
Cartoon Approximation with $$\alpha $$ α -Curvelets [PDF]
Journal of Fourier Analysis and Applications, 2015 It is well-known that curvelets provide optimal approximations for so-called cartoon images which are defined as piecewise $C^2$-functions, separated by a $C^2$ singularity curve. In this paper, we consider the more general case of piecewise $C^\beta$-functions, separated by a $C^\beta$ singularity curve for $\beta \in (1,2]$.
Philipp Grohs +2 more
exaly +3 more sources
Curvelets and Curvilinear Integrals
Journal of Approximation Theory, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David Donoho, Emmanuel Candes
exaly +3 more sources
Wavelets, ridgelets and curvelets on the sphere [PDF]
Astronomy and Astrophysics, 2006 Accepted for publication in A&A.
Y Moudden
exaly +4 more sources
Undergrowth Collagen Fibers Analysis by Fingerprint Enhancement Method. [PDF]
Biol CellCollagen fibers detected and analysed by the fingerprint enhancement algorithm. ABSTRACT Collagen is a key protein in mammals that maintains structural integrity within tissues. A failure in fibrillar collagen reorganization can induce cancer or fibrosis formation, such as in spinal cord injury (SCI), where the healing process after the initial trauma ...
Manesco C +6 more
europepmc +2 more sources
Second-Generation Curvelets on the Sphere [PDF]
IEEE Transactions on Signal Processing, 2017 Curvelets are efficient to represent highly anisotropic signal content, such as a local linear and curvilinear structure. First-generation curvelets on the sphere, however, suffered from blocking artefacts. We present a new second-generation curvelet transform, where scale-discretised curvelets are constructed directly on the sphere.
Boris Leistedt +2 more
exaly +4 more sources
Curvelets and Fourier Integral Operators
Comptes Rendus Mathematique, 2003 A recent body of work introduced new tight-frames of curvelets E. Candès, D. Donoho, in: (i) Curvelets – a suprisingly effective nonadaptive representation for objects with edges (A. Cohen, C. Rabut, L. Schumaker (Eds.)), Vanderbilt University Press, Nashville, 2000, pp. 105–120; (ii)
Laurent Demanet, Emmanuel Candes
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CURVELET BASED U-NET FRAMEWORK FOR BUILDING FOOTPRINT IDENTIFICATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 This paper proposes a multiresolution based U-net composite architecture for segmentation of remotely sensed images for building footprint identification.
R. A. Ansari, W. Thomas
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Central and Periodic Multi-Scale Discrete Radon Transforms
Applied Sciences, 2021 The multi-scale discrete Radon transform (DRT) calculates, with linearithmic complexity, the summation of pixels, through a set of discrete lines, covering all possible slopes and intercepts in an image, exclusively with integer arithmetic operations. An
Óscar Gómez-Cárdenes +3 more
doaj +1 more source
Noise Filtering of Remotely Sensed Images using Iterative Thresholding of Wavelet and Curvelet Transforms [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014 This article presents techniques for noise filtering of remotely sensed images based on Multi-resolution Analysis (MRA). Multiresolution techniques provide a coarse-to-fine and scale-invariant decomposition of images for image interpretation.
R. A. Ansari, B. K. Mohan
doaj +1 more source