Results 101 to 110 of about 6,876,175 (322)
Advanced Functional Materials, EarlyView.Gold bipyramids can act as efficient plasmonic nanoheaters, but they often reshape during laser heating. This study shows that oxygen nanobubbles drive oxidative etching and that surface ligands control stability. CTAB‐ and citrate‐coated particles blunt and lose optical performance, whereas polystyrene sulfonate preserves shape and heating by ...
Irene López‐Sicilia +7 more
wiley +1 more source
Multi-task learning with self-learning weight for image denoising
Journal of Engineering and Applied ScienceBackground Image denoising technology removes noise from the corrupted image by utilizing different features between image and noise. Convolutional neural network (CNN)-based algorithms have been the concern of the recent progress on diverse image ...
Qian Xiang, Yong Tang, Xiangyang Zhou
doaj +1 more source
ANALYSIS AND PREDICTION OF FILTERING EFFICIENCY USING NO-REFERENCE IMAGE VISUAL QUALITY METRICS
Радіоелектронні і комп'ютерні системи, 2018 Images are subject to noise during acquisition, transmission and processing. Image denoising is highly desirable, not only to provide better visual quality, but also to improve performance of the subsequent operations such as compression, segmentation ...
Андрей Сергеевич Рубель +1 more
doaj +1 more source
A Second-Order Method for Removing Mixed Noise from Remote Sensing Images
Sensors, 2023 Remote sensing image denoising is of great significance for the subsequent use and research of images. Gaussian noise and salt-and-pepper noise are prevalent noises in images.
Ying Zhou +6 more
doaj +1 more source
Enhanced CNN for image denoising
, 2019 Owing to flexible architectures of deep convolutional neural networks (CNNs), CNNs are successfully used for image denoising. However, they suffer from the following drawbacks: (i) deep network architecture is very difficult to train.
Fei, Lunke +5 more
core +1 more source
Advanced Healthcare Materials, EarlyView.Implantable optoelectrical devices are an effective resource for the modulation and monitoring of neural activity with high spatiotemporal resolution. This review discusses current challenges faced by these devices and outlines future perspectives for the development of next‐generation neural interfaces targeting chronic, multisite, and multimodal ...
Stella Aslanoglou +4 more
wiley +1 more source
A New Nonlinear Diffusion Equation Model for Noisy Image Segmentation
Advances in Mathematical Physics, 2016 Image segmentation and image denoising are two important and fundamental topics in the field of image processing. Geometric active contour model based on level set method can deal with the problem of image segmentation, but it does not consider the ...
Bo Chen +5 more
doaj +1 more source
Deep Learning on Image Denoising: An overview [PDF]
Neural Networks, 2019 Deep learning techniques have received much attention in the area of image denoising. However, there are substantial differences in the various types of deep learning methods dealing with image denoising.
Chunwei Tian +5 more
semanticscholar +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
Advanced Materials, EarlyView.This review provides an overview of triboelectric nanogenerator (TENG)–based biomedical applications by classifying studies into electronic and ionic systems across attachable and implantable platforms. It summarizes key material choices, device structures, and working mechanisms that characterize current TENG‐based research, and outlines six future ...
Kyongtae Choi +12 more
wiley +1 more source