Results 151 to 160 of about 17,318 (265)

Application of Convolutional Neural Networks for Parallel Multi-Scale Feature Extraction in Noise Image Denoising

open access: yesIEEE Access
Although deep learning techniques have made significant advances in the field of images, existing methods still face challenges in processing complex, noisy images.
Yiming Li, Tao Xie, Dongdong Mei
doaj   +1 more source

Wavelet transform based error concealment approach for image denoising

open access: yes, 2006
Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in ...
Kanhirodan, Rajan, Gupta, Pradeep K
core  

Planelets: A New Analysis Tool For Planar Feature Extraction [PDF]

open access: yes, 2004
Locally planar structures, formed by sweeping edges of objects, are commonly found in video sequences and convey most of the useful information. In this paper, the issue of efficient representation of such structures is addressed.
Yao, Zhen   +5 more
core  

Comparison of alternative image representations in the context of SAR change detection

open access: yes, 2010
This article compares four different alternative image representations in the context of a structure-based change detection. The framework is taken from the already published Curvelet-based change detection approach.
Roth, Achim   +7 more
core   +1 more source

Field‐Free Spin‐Splitting‐Torque Driven Stochastic Neuron Mimicking the Neuromorphic Imagination for High‐Performance Recognition

open access: yesAdvanced Science, EarlyView.
The human brain's imagination, which enables autonomous driving hazard avoidance by completing missing visual information, relies on Gaussian‐stochastic neuron. We report the altermagnetic RuO2 spintronic neurons integrating field‐free switching and intrinsic Gaussian stochasticity, building an all‐spin ANN for high‐quality image repairing and high ...
Junwei Zeng   +9 more
wiley   +1 more source

Burst image denoising [PDF]

open access: yes, 2019
Modern smartphone images go through very heavy image processing before they are, for example stored, transmitted or presented on the screen. Image denoising, a process of removing noise, is one of the very first steps in smartphone image processing ...
Tanskanen, Olli
core  

Diffusion‐Based Generative Model With Scaffold‐Hopping Strategy Yields Highly Potent Bioactive Molecules

open access: yesAdvanced Science, EarlyView.
SMarT‐Diff introduces a multi‐objective generative paradigm that integrates scaffold hopping with structure‐aware scoring to enable controlled exploration beyond the training distribution. The framework consistently balances drug‐likeness, synthesizes accessibility and bioactivity, yielding chemically diverse candidates with enhanced properties.
Yuwei Yang   +8 more
wiley   +1 more source

Affine non-local means image denoising

open access: yes, 2017
This work presents an extension of the Non-Local Means denoising method, that effectively exploits the affine invariant self-similarities present in images of real scenes.
Coloma Ballester   +3 more
core   +1 more source

Large‐Scale Growth of Self‐Poled Ferroelectric Rashba Semiconductor α‐GeTe(111) Thin Films: A Crucial Step Towards Future CMOS‐Compatible Ferroelectric Spintronic Devices

open access: yesAdvanced Science, EarlyView.
Ferroelectric Rashba semiconductors promise ultralow‐power devices but lack industry‐quality films. This work demonstrates CMOS‐compatible fabrication of high‐quality α‐GeTe(111) films via magnetron sputtering, enabled by a 5 nm Sb2Te3 seed layer. Structural and ferroelectric analyses show robust, switchable polarization comparable to MBE films, paving
Jules Lagrave   +14 more
wiley   +1 more source

Efficient real-world image denoising using multi-scale gaussian pyramids

open access: yesScientific Reports
The field of image denoising has undergone significant advancements over the years. Recently, Convolutional Neural Networks (CNN) based denoising methods have shown remarkable performance in image denoising.
Asha Rani, Rosepreet Kaur Bhogal
doaj   +1 more source

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