Results 11 to 20 of about 1,165,616 (316)
IEEE Access, 2017 Image fusion is a well-recognized and a conventional field of image processing. Image fusion provides an efficient way of enhancing and combining pixel-level data resulting in highly informative data for human perception as compared with individual input
Ayush Dogra, Bhawna Goyal, Sunil Agrawal
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Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary [PDF]
Entropy, 2021 Multi-focus image fusion is an important method used to combine the focused parts from source multi-focus images into a single full-focus image. Currently, to address the problem of multi-focus image fusion, the key is on how to accurately detect the ...
Hui Wan +3 more
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Parameter‐adaptive nighttime image enhancement with multi‐scale decomposition
IET Computer Vision, 2016 As a challenging problem, image enhancement plays an important role in computer vision applications and has been widely studied. As one of the most difficult issues of image enhancement, outdoor nighttime image enhancement suffers from noise ...
Shuhang Wang, Jin Zheng, Bo Li
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Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition [PDF]
Sensors, 2015 A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate ...
Naveed ur Rehman +5 more
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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
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AMDCnet: attention-gate-based multi-scale decomposition and collaboration network for long-term time series forecasting [PDF]
Frontiers in Artificial IntelligenceIntroductionTime series analysis plays a critical role in various applications, including sensor data monitoring, weather forecasting, economic predictions, and network traffic management. While traditional methods primarily focus on modeling time series
Shikang Hou +4 more
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Systematic multi-scale decomposition of ocean variability using machine learning.
Chaos: An Interdisciplinary Journal of Nonlinear Science, 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.
C. Franzke, F. Gugole, S. Juricke
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Subspace Decomposition based DNN algorithm for elliptic type multi-scale PDEs [PDF]
SSRN Electronic Journal, 2021 While deep learning algorithms demonstrate a great potential in scientific computing, its application to multi-scale problems remains to be a big challenge.
Xi-An Li, Z. Xu, Lei Zhang
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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.
Guanlei Xu +4 more
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A multi-scale CNN-GRU fusion model with stationary wavelet transform for 14-day ahead dam water level prediction [PDF]
Scientific ReportsThis study investigated the effectiveness of SWT data decomposition in enhancing CNN-GRU early-, slow- and late fusion models for 14-day ahead water level prediction at the Klang Gates Dam.
Kai Wen Ng +5 more
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