A Review of EEG-based Localization of Epileptic Seizure Foci: Common Points with Multimodal Fusion of Brain Data. [PDF]
Tajmirriahi M, Rabbani H.
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Linear transforms for Fourier data on the sphere: application to high angular resolution diffusion MRI of the brain. [PDF]
Haldar JP, Leahy RM.
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Tight frames of k-plane ridgelets and the problem of representing objects that are smooth away from d-dimensional singularities in Rn. [PDF]
Donoho DL.
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A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging. [PDF]
Ning L +6 more
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Rotation-invariant multiresolution texture analysis using radon and wavelet transforms. [PDF]
Jafari-Khouzani K, Soltanian-Zadeh H.
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CerviXpert: A multi-structural convolutional neural network for predicting cervix type and cervical cell abnormalities. [PDF]
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Arbitrarily Shape Object-based Video Coding Technology by Finite Ridgelet Transform
2018 IEEE International Conference on Information and Automation (ICIA), 2018Video object coding is one of the most important functions of MPEG4. In this paper, we propose a new object based finite ridgelet transform for arbitrary shape video coding, including static and video objects. The method uses the shape adaptive finite ridgelet transform (SA Ridgelet transform) for the object coding, and uses the more efficient lifting ...
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Efficient Blind Image Separation Using Finite Ridgelet Transform
2013 23rd International Conference on Computer Theory and Applications (ICCTA), 2013This paper deals with the problem of blind separation of digital images from noisy mixtures. It proposes the application of a blind separation algorithm on Ridgelet Transform (RT) of the mixed images, instead of performing the separation on the mixtures in the time domain.
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The Finite Ridgelet Transform for Defeat Detection of Quill
Advanced Materials Research, 2011A defeat detection method for quill using the finite ridgelet transform is mentioned. This method reduce the average gray values of quill and analytic statistics methods are used in ridgelet transform according to points of quill. After ridgelet transform the linear singularity is further highlighted and the quantization errors caused by cutting image ...
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An Approximate Finite Ridgelet Transform Algorithm for SAR Image Segmentation
2006 8th international Conference on Signal Processing, 2006The finite ridgelet transform proposed by Donoho has successful application in edge detection and segmentation of images with high-noise, but it has a drawback which is due to annoying "wrap-around" effect to the finite Radon transform. As a result, it may also produce "alias" edges and "holes" in the reconstructed image.
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