Results 31 to 40 of about 1,028 (168)
Quantum algorithms using the curvelet transform [PDF]
Proceedings of the forty-first annual ACM symposium on Theory of computing, 2009 64 pages, 4 figures; improved algorithm and lower bound for finding the center of a radial function; revised presentation; to appear in STOC ...
openaire +3 more sources
Effectiveness of Image Curvelet Transform Coefficients for Image Denoising [PDF]
Al-Rafidain Journal of Computer Sciences and MathematicsIn this research, we investigate the effect of image curvelet transform coefficients in image denoising. The curvelet transform applies to input images, resulting in a set of curvelet coefficients that capture different frequency and directional ...
Hadia Abdulla +2 more
doaj +1 more source
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
doaj +1 more source
FETAL ULTRASOUND IMAGE DENOISING USING CURVELET TRANSFORM [PDF]
ICTACT Journal on Image and Video Processing, 2015 The random speckle noise in the acquired fetal ultrasound images is caused by the interference of reflected ultrasound wave fronts. The presence of speckle noise will degrade the quality of the image and even hide image details, which in turn affect the ...
J. Nithya, M. Madheswaran
doaj
Advanced Intelligent Systems, Volume 8, Issue 7, July 2026.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Iterative Deblending of off-the-Grid Simultaneous Source Data
IEEE Access, 2021 Simultaneous source acquisition can enhance the seismic data quality or improve the field acquisition efficiency. However, one of the disadvantages is that the simultaneous source data are often obtained on a non-uniform sampled grid in realistic ...
Hua Zhang +3 more
doaj +1 more source
Optimized Hybrid Deep Learning‐Based FPGA Accelerators for Denoising of Ultrasound Breast Images
IET Circuits, Devices &Systems, Volume 2026, Issue 1, 2026.This paper introduces a novel image‐denoising technique that integrates a hybrid deep learning (DL) model with a self‐improved orca predation (SOP) strategy. This hybrid model improves denoising performance by integrating a Convolutional Neural Network (CNN) with Bidirectional Long Short‐Term Memory (Bi‐LSTM).
K. Janaki +4 more
wiley +1 more source
Face Recognition Using Curvelet Transform
, 2010 This paper presents a new method for the problem of human face recognition from still images. This is based on a multiresolution analysis tool called Digital Curvelet Transform. Curvelet transform has better directional and edge representation abilities than wavelets.
Hana Hejazi, Mohammed Alhanjouri
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IET Image Processing, Volume 20, Issue 1, January/December 2026.This study presents a robust facial recognition framework based on a unified optimised feature vector that fuses handcrafted descriptors and deep learning embeddings. Using binary grey wolf optimisation for feature selection, the approach reduces redundancy while preserving discriminative power.
Farid Ayeche, Adel Alti
wiley +1 more source
Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.Brain tumors develop due to the unregulated proliferation of nerve tissues. Nonetheless, despite progress in deep learning models for medical image analysis, the precise segmentation of tumor patches and categorization of tumor types remain unresolved.
A. Ashwini +5 more
wiley +1 more source