Smooth Affine Model for the Framed Correspondences Spectrum

Due to the characteristics of low signal-to-noise ratio and low contrast, low-light images will have problems such as color distortion, low visibility, and accompanying noise, which will cause the accuracy of the target detection problem to drop or even miss the detection target. However, recalibrating the dataset for this type of image will face problems such as increased cost or reduced model robustness. To solve this kind of problem, we propose a low-light image enhancement model based on deep learning. In this paper, the feature extraction is guided by the illumination map and noise map, and then the neural network is trained to predict the local affine model coefficients in the bilateral space. Through these methods, our network can effectively denoise and enhance images. We have conducted extensive experiments on the LOL datasets, and the results show that, compared with traditional image enhancement algorithms, the model is superior to traditional methods in image quality and speed.

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Optimal Integrated Energy System Planning with DG Uncertainty Affine Model and Carbon Emissions Charges

IEEE Transactions on Sustainable Energy ◽

10.1109/tste.2021.3139109 ◽

2021 ◽

pp. 1-1

Author(s):

Leijiao Ge ◽

Hangxu Liu ◽

Jun Yan ◽

Xinshan Zhu ◽

Shuai Zhang ◽

...

Keyword(s):

Carbon Emissions ◽

Energy System ◽

System Planning ◽

Affine Model ◽

Integrated Energy System ◽

Energy System Planning

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A Note on Geometric Factoriality

Canadian Mathematical Bulletin ◽

10.4153/cmb-1995-057-0 ◽

1995 ◽

Vol 38 (4) ◽

pp. 390-395 ◽

Cited By ~ 1

Author(s):

S. M. Bhatwadekar ◽

K. P. Russell

Keyword(s):

Finite Groups ◽

Positive Answer ◽

Integral Representations ◽

Perfect Field ◽

Polynomial Algebras ◽

Representations Of Finite Groups ◽

Smooth Affine

AbstractLet k: be a perfect field such that is solvable over k. We show that a smooth, affine, factorial surface birationally dominated by affine 2-space is geometrically factorial and hence isomorphic to . The result is useful in the study of subalgebras of polynomial algebras. The condition of solvability would be unnecessary if a question we pose on integral representations of finite groups has a positive answer.

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Affine Versus Non-Affine Fibril Kinematics in Collagen Networks: Theoretical Studies of Network Behavior

Journal of Biomechanical Engineering ◽

10.1115/1.2165699 ◽

2005 ◽

Vol 128 (2) ◽

pp. 259-270 ◽

Cited By ~ 142

Author(s):

Preethi L. Chandran ◽

Victor H. Barocas

Keyword(s):

Network Model ◽

Constitutive Modeling ◽

Load Transfer ◽

Critical Role ◽

Affine Model ◽

Tissue Equivalents ◽

Scale Models ◽

Macroscopic Deformation ◽

The Individual ◽

Open Question

The microstructure of tissues and tissue equivalents (TEs) plays a critical role in determining the mechanical properties thereof. One of the key challenges in constitutive modeling of TEs is incorporating the kinematics at both the macroscopic and the microscopic scale. Models of fibrous microstructure commonly assume fibrils to move homogeneously, that is affine with the macroscopic deformation. While intuitive for situations of fibril-matrix load transfer, the relevance of the affine assumption is less clear when primary load transfer is from fibril to fibril. The microstructure of TEs is a hydrated network of collagen fibrils, making its microstructural kinematics an open question. Numerical simulation of uniaxial extensile behavior in planar TE networks was performed with fibril kinematics dictated by the network model and by the affine model. The average fibril orientation evolved similarly with strain for both models. The individual fibril kinematics, however, were markedly different. There was no correlation between fibril strain and orientation in the network model, and fibril strains were contained by extensive reorientation. As a result, the macroscopic stress given by the network model was roughly threefold lower than the affine model. Also, the network model showed a toe region, where fibril reorientation precluded the development of significant fibril strain. We conclude that network fibril kinematics are not governed by affine principles, an important consideration in the understanding of tissue and TE mechanics, especially when load bearing is primarily by an interconnected fibril network.

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Affine varieties, singularities and the growth rate of wrapped Floer cohomology

Journal of Topology and Analysis ◽

10.1142/s1793525318500176 ◽

2018 ◽

Vol 10 (03) ◽

pp. 493-530

Author(s):

Mark McLean

Keyword(s):

Growth Rate ◽

Cotangent Bundle ◽

Betti Numbers ◽

Symplectic Manifolds ◽

Isolated Singularity ◽

Contact Manifolds ◽

Floer Cohomology ◽

Complex Singularities ◽

Smooth Affine ◽

Simply Connected

In this paper, we give partial answers to the following questions: Which contact manifolds are contactomorphic to links of isolated complex singularities? Which symplectic manifolds are symplectomorphic to smooth affine varieties? The invariant that we will use to distinguish such manifolds is called the growth rate of wrapped Floer cohomology. Using this invariant we show that if [Formula: see text] is a simply connected manifold whose unit cotangent bundle is contactomorphic to the link of an isolated singularity or whose cotangent bundle is symplectomorphic to a smooth affine variety then M must be rationally elliptic and so it must have certain bounds on its Betti numbers.

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