In this paper, we propose a new co-saliency detection based on weighted low-rank matrix fusion. Firstly, a multi-scale superpixel pyramid are segmented by different thresholds using superpixel segmentation algorithms, and we use a weighted low-rank matrix recovery model to generate corresponding ...
Achlioptas D, McSherry F (2007) Fast computation of low-rank matrix approximations. J ACM 54:1–19 Article MathSciNet Google Scholar Cai M, Shen X, Abhadiomhen SE, Cai Y, Tian S (2023) Robust dimensionality reduction via low-rank Laplacian graph learning. ACM Trans Intell Syst Techno...
Most of the conventional low-rank matrix approxi... Eunwoo,Kim,Minsik,... - 《IEEE Transactions on Neural Networks & Learning Systems》 被引量: 24发表: 2015年 Using Sparse Parts in Fused Information to Enhance Performance in Latent Low-Rank Representation-Based Fusion of Visible and Infrared...
Recently, low-rank matrix recovery has been demonstrated to be an effective tool in hyperspectral images (HSIs) denoising. However, the previous low-rank matrix recovery method with a window of the fixed-shape cannot adaptively exploit spatial structure information and nonlocal similarity. In this ...
The low-rank matrix approximation problem with respect to the component-wise \\ell_1 \\ell_1 -norm ( \\ell_1 \\ell_1 -LRA), which is closely related to rob... N Gillis,SA Vavasis - 《Mathematics》 被引量: 21发表: 2015年 A novel speech enhancement method based on constrained low...
2022年在AIGC时代到来之后,LoRA(Low-Rank Adaptation)无疑成为了AI绘画领域中与Stable Diffusion(简称SD)系列配合使用最多的模型,SD模型+LoRA模型的组合,不仅创造了很多脑洞大开的AI绘画风格、人物以及概念,而且大幅降低了AI绘画的成本,提高了AI绘画的多样性和灵活性,让各行各业的人都真真切切地感受到了AI绘画的...
内容来自Andrew老师课程Machine Learning的第九章内容的Low Rank Matrix Factorization部分。 一、Vectorization: Low Rank Matric Factorization(向量化: 低秩矩阵分解) 我们仍然使用之前movie的例子: 将这些数据写成矩阵的形式,即右边的Y矩阵,又因为用户j对电影i的评分预测值为: 因此Y矩阵对应... ...
Low-Rank Matrix Fitting Based on Subspace Perturbation Analysis with Applications to Structure from Motion IEEE Transactions on Pattern Analysis & Machine IntelligenceH. Jia, A.M. Martinez, Low-rank matrix fitting based on subspace perturbation analysis with ... H Jia,AM Martinez - 《IEEE ...
A collaborative image segmentation framework, called multi-task low-rank affinity pursuit, is presented for such a purpose. Given an image described with multiple types of features, we aim at inferring a unified affinity matrix that implicitly encodes the segmentation of the image. This is achieved...
从一系列相关的图像中找到相同区域的patch,那么这些patch都存在一个非常低维的子空间,那么这些patch聚类后,就能得到一个低秩矩阵(low-rank matrix),这样的好处是可以使用ALM-ADM策略来解决图像还原问题 本文提出一种衡量patch与transmission layer之间相似性的matric,基于图像强度和梯度。