Results 21 to 30 of about 8,888,697 (293)
IEEE Access, 2021 Numerous studies employ multi-scale decomposition to improve the prediction performance of neural networks, but the grounds for selecting the decomposition algorithm are not explained, and the effects of decomposition algorithms on other performance of ...
Haichao Huang +4 more
doaj +1 more source
Multi-Exposure Image Fusion Algorithm Based on Improved Weight Function
Frontiers in Neurorobotics, 2022 High-dynamic-range (HDR) image has a wide range of applications, but its access is limited. Multi-exposure image fusion techniques have been widely concerned because they can obtain images similar to HDR images. In order to solve the detail loss of multi-
Ke Xu +3 more
doaj +1 more source
FSADFuse: A Novel Fusion Approach to Infrared and Visible Images
IEEE Access, 2021 To address the problems of edge blur and weak detail resolution when fusing infrared and visible images with traditional methods, a novel image fusion approach based on fast super-resolution convolutional neural network and anisotropic diffusion is ...
Shuai Hao +5 more
doaj +1 more source
IET Image Processing, 2021 Fusion and noise suppression of medical images are becoming increasingly difficult to be ignored in image processing, and this technique provides abundant information for the clinical diagnosis and treatment.
Xuefeng Zhang, Hui Yan
doaj +1 more source
The Study of Feature Extraction Method Based on Multi-scale Morphological Spectrum Entropy
Chemical Engineering Transactions, 2016 Multi-scale morphological decomposition is a decomposition method being proposed based on the basic theory of multi-scale morphology. Using from small to large scale of structural elements to deal with different “Scale domain”, thus the original signal ...
H.M. Ge, L. Chen, J. Liang
doaj +1 more source
Systematic multi-scale decomposition of ocean variability using machine learning [PDF]
, 2022 Multi-scale systems, such as the climate system, the atmosphere, and the ocean, are hard to understand and predict due to their intrinsic nonlinearities and chaotic behavior.
Juricke, Stephan +7 more
core +1 more source
Multi-scale proper orthogonal decomposition of complex fluid flows [PDF]
Journal of Fluid Mechanics, 2019 Data-driven decompositions are becoming essential tools in fluid dynamics, allowing for tracking the evolution of coherent patterns in large datasets, and for constructing low-order models of complex phenomena. In this work, we analyse the main limits of two popular decompositions, namely the proper orthogonal decomposition (POD) and the dynamic mode ...
M. A. Mendez, M. Balabane, J.-M. Buchlin
openaire +2 more sources
Multi-Scale Modelling of a Solar Reactor for the High-Temperature Step of a Sulphur-Iodine-Based Water Splitting Cycle [PDF]
, 2011 The 3-step sulphur-iodine-based thermochemical cycle for splitting water is considered. The high temperature step of the closed-material cycle consists of evaporation, decomposition, and reduction of sulphuric acid to SO2 using concentrated solar process
Roeb, Martin +11 more
core +2 more sources
Multi-scale Image Decomposition Using a Local Statistical Edge Model [PDF]
2021 IEEE 7th International Conference on Virtual Reality (ICVR), 2021 We present a progressive image decomposition method based on a novel non-linear filter named Sub-window Variance filter. Our method is specifically designed for image detail enhancement purpose; this application requires extraction of image details which are small in terms of both spatial and variation scales.
openaire +2 more sources
Unified framework for multi‐scale decomposition and applications
The Journal of Engineering, 2017 Since real‐world digital images differ in thousands ways, an adaptive multi‐scale decomposition scheme adapting to images is increasingly urgently required for image analysis and applications. In this paper, a unified framework for multi‐scale decomposition is developed.
Xu Guanlei +4 more
openaire +1 more source