Search Results for author:
Found 15 papers, 7 papers with code
Face recognition via compact second order image gradient orientations
The second order image gradient orientations (SOIGO) can mitigate the adverse effect of noises in face images.
MOON: Multi-Hash Codes Joint Learning for Cross-Media Retrieval
To this end, we develop a novel Multiple hash cOdes jOint learNing method (MOON) for cross-media retrieval.
Affine Non-negative Collaborative Representation Based Pattern Classification
Moreover, ANCR introduces an affine constraint to better represent the data from affine subspaces.
Learning efficient structured dictionary for image classification
Recent years have witnessed the success of dictionary learning (DL) based approaches in the domain of pattern classification.
Face Verification via learning the kernel matrix
The method CSKDA needs to choose a proper kernel function through many experiments, while the new method could learn the kernel from data automatically which could save a lot of time and have the robust performance.
Multiplication fusion of sparse and collaborative-competitive representation for image classification
Firstly, the coefficients of the test sample are obtained by SRC and CCRC, respectively.
A sparsity augmented probabilistic collaborative representation based classification method
In order to enhance the performance of image recognition, a sparsity augmented probabilistic collaborative representation based classification (SA-ProCRC) method is presented.
A Compared Study Between Some Subspace Based Algorithms
The technology of face recognition has made some progress in recent years.
Research on Clustering Performance of Sparse Subspace Clustering
Recently, sparse subspace clustering has been a valid tool to deal with high-dimensional data.
Collaborative representation-based robust face recognition by discriminative low-rank representation
Collaborative representation based classification (CRC) method is exploited in our proposed method which has closed-form solution.
Low-rank representations with incoherent dictionary for face recognition
Face recognition remains a hot topic in computer vision, and it is challenging to tackle the problem that both the training and testing images are corrupted.
Face Recognition via Locality Constrained Low Rank Representation and Dictionary Learning
First, a low-rank representation is introduced to handle the possible contamination of the training as well as test data.
Learning a Representation with the Block-Diagonal Structure for Pattern Classification
To counteract this problem, we propose an approach that learns Representation with Block-Diagonal Structure (RBDS) for robust image recognition.
Locality Constraint Dictionary Learning with Support Vector for Pattern Classification
In this paper, we propose a locality constraint dictionary learning with support vector discriminative term (LCDL-SV), in which the locality information is preserved by employing the graph Laplacian matrix of the learned dictionary.
Class-specific residual constraint non-negative representation for pattern classification
Representation based classification method (RBCM) remains one of the hottest topics in the community of pattern recognition, and the recently proposed non-negative representation based classification (NRC) achieved impressive recognition results in various classification tasks.
