Results 81 to 90 of about 116,500 (328)
Materials and System Design for Self‐Decision Bioelectronic Systems
Advanced Materials, EarlyView.This review highlights how self‐decision bioelectronic systems integrate sensing, computation, and therapy into autonomous, closed‐loop platforms that continuously monitor and treat diseases, marking a major step toward intelligent, self‐regulating healthcare technologies.
Qiankun Zeng +9 more
wiley +1 more source
Fractal-wavelet image denoising revisited [PDF]
IEEE Transactions on Image Processing, 2006 The essence of fractal image denoising is to predict the fractal code of a noiseless image from its noisy observation. From the predicted fractal code, one can generate an estimate of the original image. We show how well fractal-wavelet denoising predicts parent wavelet subtress of the noiseless image.
Mohsen, Ghazel +2 more
openaire +2 more sources
Ductility Tuning via Cluster Network Characteristics of Porous Components
Advanced Materials Technologies, EarlyView.Network optimization via cluster characteristics induced by interaction of stress concentration is proposed, demonstrating increased cluster size and dispersion in non‐uniform porous components. The optimized structures exhibit, for the first time, that enhanced ductility and damage progression is controllable through zigzag cluster network designed by
Ryota Toyoba +4 more
wiley +1 more source
Fully Symmetric Convolutional Network for Effective Image Denoising
Applied Sciences, 2019 Neural-network-based image denoising is one of the promising approaches to deal with problems in image processing. In this work, a deep fully symmetric convolutional⁻deconvolutional neural network (FSCN) is proposed for image denoising.
Steffi Agino Priyanka, Yuan-Kai Wang
doaj +1 more source
TELKOMNIKA Indonesian Journal of Electrical Engineering, 2014 A Mixed Window Shrink and BayesShrink Image Denoising Algorithm Based on Curve let Transform is proposed in this paper. Curve let transform is effective in presenting line and surface property of image. In the proposed algorithm, Curvelet transform is employed for the first stage, then according the theory of image demising method based on Wavelet ...
Zhang Ye, Jia Meng
openaire +1 more source
DCT Image Denoising: a Simple and Effective Image Denoising Algorithm [PDF]
Image Processing On Line, 2011 This work presents a simple but effective denoising algorithm using a local DCT thresholding. This thresholding is applied separately to each color channel after decorrelation. Due to its simplicity and excellent performance, this contribution can be considered as a baseline for comparison and lower bound of performance for newly developed techniques.
Guoshen Yu, Guillermo Sapiro
openaire +2 more sources
Progress and Prospects of Persistent Luminescent Nanocrystals in Biomedical Applications
Advanced Optical Materials, EarlyView.This review summarizes recent progress in materials‐level control of persistent luminescence, including mechanistic understanding, wavelength/intensity tuning, and activation strategies, as well as emerging biomedical applications in imaging, biosensing, cell tracking, optogenetic stimulation, and biophotochemical activation.
Peng Pei +5 more
wiley +1 more source
Medical Image Denoising using Adaptive Threshold Based on Contourlet Transform
, 2011 Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using contourlet transform.
Prasad, KVSVR, Satheesh, S.
core +1 more source
Nonlocal Adaptive Image Denoising Model [PDF]
Mathematical Problems in Engineering, 2013 When denoising with the method of Weickert’s anisotropic diffusion equation, the textures and details will be compromised. A fidelity term is added to Weickert’s equation, and the coefficient of fidelity term will vary adaptively with the instant image, which makes the diffusion term and the fidelity term come to a better compromise.
Sun, Xiaoli, Xu, Chen, Li, Min
openaire +1 more source
Excitonic Landscapes in Monolayer Lateral Heterostructures Revealed by Unsupervised Machine Learning
Advanced Optical Materials, EarlyView.Hyperspectral photoluminescence data from graded MoxW1 − xS2 alloys and monolayer MoS2–WS2 lateral heterostructures are analyzed using unsupervised machine learning. The combined use of PCA, t‐SNE, and DBSCAN uncovers distinct excitonic regions that trace how composition, strain, and defects modulate optical responses in these 2D materials.
Maninder Kaur +4 more
wiley +1 more source