Results 251 to 260 of about 1,958,095 (294)

AI-driven sustainable strength prediction and experimental evaluation of high-performance fiber-reinforced concrete incorporating metakaolin. [PDF]

Sci Rep
N S NP, P K, P S.
europepmc   +1 more source

Generating Dynamic Structures Through Physics-Based Sampling of Predicted Inter-Residue Geometries. [PDF]

Adv Sci (Weinh)
Xiang C, Wang W, Peng Z, Yang J.
europepmc   +1 more source

Visual image perception preservation through a compression-encryption framework. [PDF]

Sci Rep
Madkour ME, Soliman SE, Dessouky MI, El-Samie FEA, Elsafrawey AS, Hammad ME.   +5 more
europepmc   +1 more source

Multi Echo-Time ASL MRI Denoising via Joint Complex Low-Rank Regularization. [PDF]

Annu Int Conf IEEE Eng Med Biol Soc
Liu H, Li B, Li Y, Taso M, Detre JA, Wang Z.   +5 more
europepmc   +1 more source

A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion. [PDF]

J Comput Graph Stat
Liu X, Han X, Chi EC, Nadler B.
europepmc   +1 more source

Weighted Nuclear Norm Minimization With Application to Image Denoising [PDF]

2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
As a convex relaxation of the low rank matrix factorization problem, the nuclear norm minimization has been attracting significant research interest in recent years. The standard nuclear norm minimization regularizes each singular value equally to pursue the convexity of the objective function.
Shuhang Gu, Wangmeng Zuo
exaly   +5 more sources

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Uniqueness in Nuclear Norm Minimization: Flatness of the Nuclear Norm Sphere and Simultaneous Polarization

Journal of Optimization Theory and Applications, 2023
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tim Hoheisel, Elliot Paquette
openaire   +2 more sources

Feature and Nuclear Norm Minimization for Matrix Completion

IEEE Transactions on Knowledge and Data Engineering, 2022
Matrix completion, whose goal is to recover a matrix from a few entries observed, is a fundamental model behind many applications. Our study shows that, in many applications, the to-be-complete matrix can be represented as the sum of a low-rank matrix and a sparse matrix associating with side information matrices. The low-rank matrix depicts the global
Mengyun Yang, Yaohang Li, Jianxin Wang 0001   +2 more
openaire   +1 more source

Cauchy Noise Removal by Weighted Nuclear Norm Minimization

Journal of Scientific Computing, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Geonwoo Kim, Junghee Cho, Myungjoo Kang
openaire   +3 more sources