a weighted block cooperative sparse representation algorithm is proposed based on visual saliency dictionary.First,the algorithm uses the biological visual attention mechanism to quickly and accurately obtain the face salient target and constructs the visual salient dictionary.Then,a block cooperation ...
we propose a new method called weighted block-sparse low rank representation (WBSLRR) which considers the available prior knowledge while learning a low rank data representation, and also develop a simple but effective approach to obtain the clustering result of faces. Moreover, after using several...
Keywords: sparseclassification;weightednearestneighborclasses;linearrepresentation;PCA;blocksparserepresen tation 1 引言 人脸识别因其应用广泛且典型而成为模式识 别和机器视觉领域的研究重点,MaYi等首先将稀疏 表示应用于人脸识别,由于其下采样和协同稀疏表
Finally, the weighted sparse representation based classification machine learning strategy is adopted to predict SIPs. Promising experimental results reveal that the constructed model is feasible and efficient when dealing with the classification task of interacting and non-interacting pairs of protein ...
3. It consists of a multi-head self-attention (MSA) block, a multi-layer perceptron (MLP) layer, and two normalization layers. Figure 3 Illustration of the spectral transformer encoder and transformer decoder. MLP refers to multi-layer perceptron and norm refers to normalization. The input \...
{2}+k\). We then used this vector as anldimensional representation of the overall pattern of community structure and measured these vectors similarity and distance to our consensus models. For this analysis, we used the block matrix of average strength between communities, as opposed to total ...
The matrix-based scheme such as adjacency matrix is often have large numbers of zero entries, specially when the graph is sparse. Various formats such as compressed sparse row (CSR), compressed sparse column (CSC), and block sparse row (BSR), K2 − Tree are developed to reduce memory ...
One research branch is patch group-based sparse representation [2,13,17–26]. For example, Dabov et al. [17] formulated a block matching with 3D filtering (BM3D) denoising algorithm. Show abstract Low-rank with sparsity constraints for image denoising 2023, Information Sciences Show abstract ...
Image smoothing is a fundamental building block in many tasks of both computer vision and computational photography. It thus attracts much research interest and has been studied for decades with a number of approaches proposed. There are two kinds of approaches that have been well studied: the we...
Lu C, Feng J, Lin Z, Mei T, Yan S (2019) Subspace clustering by block diagonal representation. IEEE Trans Pattern Anal Mach Intell 41(2):487–501 Article Google Scholar Tang C, Liu X, Li M, Wang P, Chen J, Wang L, Li W (2018) Robust unsupervised feature selection via dual ...