Results 11 to 20 of about 1,107 (155)
, 2009 Glossary WT1D The one-dimensional Wavelet Transform as defined in [1]. See also [2] in this volume. WT2D The two-dimensional Wavelet Transform. Discrete Ridgelet Trasnform (DRT) The discrete implementation of the continuous Ridgelet transform. Fast Slant Stack (FSS) An algebraically exact Radon transform of data on a Cartesian grid.
Fadili, Jalal M., Starck, Jean-Luc
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Ridgelet transform on the sphere. [PDF]
CoRR, 2018 5 pages, 4 figures, matches version accepted by EUSIPCO, code available at http://www.s2let ...
Jason D. McEwen, Matthew A. Price
core +6 more sources
Discrete analytical Ridgelet transform [PDF]
Signal Processing, 2004 In this paper, we present a new implementation of the Ridgelet transform based on discrete analytical 2-D lines: the discrete analytical Ridgelet transform (DART). This transform uses the Fourier strategy for the computation of the associated discrete Radon transform.
Carré, Philippe, Andres, Eric
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IET Radar, Sonar &Navigation, Volume 17, Issue 12, Page 1743-1759, December 2023., 2023 An overview of the past and current clutter theoretical models and clutter suppression techniques in the HFSWR system is provided. The experimental results involved in the complex long‐term ionosphere observation are discussed. Special attention is paid to the correlation between the signal degradation sources and eliminating clutter techniques ...
Xiaowei Ji +3 more
wiley +1 more source
Priors in Bayesian Deep Learning: A Review
International Statistical Review, Volume 90, Issue 3, Page 563-591, December 2022., 2022 Summary While the choice of prior is one of the most critical parts of the Bayesian inference workflow, recent Bayesian deep learning models have often fallen back on vague priors, such as standard Gaussians. In this review, we highlight the importance of prior choices for Bayesian deep learning and present an overview of different priors that have ...
Vincent Fortuin
wiley +1 more source
Robust medical zero‐watermarking algorithm based on Residual‐DenseNet
IET Biometrics, Volume 11, Issue 6, Page 547-556, November 2022., 2022 Abstract To solve the problem of poor robustness of existing traditional DCT‐based medical image watermarking algorithms under geometric attacks, a novel deep learning‐based robust zero‐watermarking algorithm for medical images is proposed. A Residual‐DenseNet is designed, which took low‐frequency features after discrete cosine transformation of ...
Cheng Gong +5 more
wiley +1 more source
Statistical quality control using image intelligence: A sparse learning approach
Naval Research Logistics (NRL), Volume 69, Issue 7, Page 996-1008, October 2022., 2022 Abstract Advances in image acquisition technology have made it convenient and economic to collect large amounts of image data. In manufacturing and service industries, images are increasingly used for quality control purposes because of their ability to quickly provide information about product geometry, surface defects, and nonconforming patterns.
Yicheng Kang
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A review on short‐term load forecasting models for micro‐grid application
The Journal of Engineering, Volume 2022, Issue 7, Page 665-689, July 2022., 2022 Abstract Load forecasting (LF), particularly short‐term load forecasting (STLF), plays a vital role throughout the operation of the conventional power system. The precise modelling and complex analyses of STLF have become more significant in advanced microgrid (MG) applications.
V. Y. Kondaiah +3 more
wiley +1 more source
Multivariable passive method for detection of islanding events in renewable energy based power grids
IET Renewable Power Generation, Volume 16, Issue 3, Page 497-516, 24 February 2022., 2022 Abstract Penetration of distributed generation resources (DGR) in power grid is rapidly increasing to meet future energy demand efficiently. It helps in mitigating the problems of high carbon emission, green house effect, and increased cost of oil and natural gases.
Nagendra Kumar Swarnkar +3 more
wiley +1 more source
Pixel‐Boundary‐Dependent Segmentation Method for Early Detection of Diabetic Retinopathy
Mathematical Problems in Engineering, Volume 2022, Issue 1, 2022., 2022 Early and precise detection of diabetic retinopathy prevents vision impairments through computer‐aided clinical procedures. Identifying the symptoms and processing those by using sophisticated clinical procedures reduces hemorrhage kind of risks.
S. G. Sandhya +3 more
wiley +1 more source