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Laplace Operator in Connection to Underlying Space Structure
Laplace operator is a diverse concept throughout natural sciences. It appears in many research areas and every such area defines it accordingly based...
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Single image super-resolution with self-organization neural networks and image laplace gradient operator
At present, artificial neural networks have received wide applications in the field of image processing and image resolution because of their fast...
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LDANet: the laplace-guided detail-constrained asymmetric network for real-time semantic segmentation
The current mainstream image semantic segmentation networks often suffer from mis-segmentation, segmentation discontinuity, and high model...
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Certified coordinate selection for high-dimensional Bayesian inversion with Laplace prior
We consider high-dimensional Bayesian inverse problems with arbitrary likelihood and product-form Laplace prior for which we provide a certified...
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Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks
Parameter estimation and associated uncertainty quantification is an important problem in dynamical systems characterised by ordinary differential...
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High-Dimensional Dataset Simplification by Laplace-Beltrami Operator
With the development of the Internet and other digital technologies, the speed of data generation has become considerably faster than the speed of...
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Continual Learning with Laplace Operator Based Node-Importance Dynamic Architecture Neural Network
In this paper, we propose a continual learning method based on node-importance evaluation and a dynamic architecture model. Our method determines the...
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Revisiting convolutional neural network on graphs with polynomial approximations of Laplace–Beltrami spectral filtering
This paper revisits spectral graph convolutional neural networks (graph-CNNs) given in Defferrard (2016) and develops the Laplace–Beltrami CNN...
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Deformable shape matching with multiple complex spectral filter operator preservation
The functional maps framework has achieved remarkable success in non-rigid shape matching. However, the traditional functional map representations do...
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Icg: intensity and color gradient operator on RGB images for visual object tracking
The design of digital filters is now mostly automated with convolutional neural networks (CNNs). State-of-the-art works in tracking methods,...
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Autofocus algorithm using optimized Laplace evaluation function and enhanced mountain climbing search algorithm
In the field of digital imaging systems, autofocus plays increasingly a vital role as a key technology. Autofocus poses a great challenge due to...
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A well-conditioned method of fundamental solutions for Laplace equation
The method of fundamental solutions (MFS) is a numerical method for solving boundary value problems involving linear partial differential equations....
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Genetic Programming Symbolic Regression with Simplification-Pruning Operator for Solving Differential Equations
Differential equations (DEs) are important mathematical models for describing natural phenomena and engineering problems. Finding analytical...
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Digital Calculus Frameworks and Comparative Evaluation of Their Laplace-Beltrami Operators
Defining consistent calculus frameworks on discrete meshes is useful for processing the geometry of meshes or model numerical simulations and...
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Nonlocal Laplace Operator in a Space with the Fuzzy Partition
Differential operators play an important role in the mathematical modeling of dynamic processes and the analysis of various structures. However,...
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Non-local modelling of multiphase flow wetting and thermo-capillary flow using peridynamic differential operator
Interfaces in multiphase flows are affected by surface tension, and when temperature gradients occur in the flow domain, tangential surface tensions...
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Gaussian processes with skewed Laplace spectral mixture kernels for long-term forecasting
Long-term forecasting involves predicting a horizon that is far ahead of the last observation. It is a problem of high practical relevance, for...
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Application of canny operator threshold adaptive segmentation algorithm combined with digital image processing in tunnel face crevice extraction
The present work aims to reduce tunnel construction accidents to personnel. The threshold adaptive segmentation algorithm combined with the Canny...
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Study of Sparsification Schemes for the FEM Stiffness Matrix of Fractional Diffusion Problems
Anomalous diffusion describes various natural and social phenomena and processes in which the Brownian motion hypothesis is violated. Such problems...