Likun Huang

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Different from the existing approaches that usually utilize single view information of image sets to recognize persons, multi-view information of image sets is exploited in this paper, where a novel method called Co-Learned Multi-View Spectral Clustering (CMSC) is proposed to recognize faces based on image sets. In order to make sure that a data point under(More)
In this paper, we propose a new multi-manifold metric learning (MMML) method for the task of face recognition based on image sets. Different from most existing metric learning algorithms that learn the distance metric for measuring single images, our method aims to learn distance metrics to measure the similarity between manifold pairs. In our method, each(More)
In this paper, we propose a new collaborative reconstructionbased manifold-manifold distance (CRMMD) method for face recognition with image sets, where each gallery and probe sample is a set of face images captured from varying poses, illuminations and expressions. Given each face image set, we first model it as a nonlinear manifold and then the recognition(More)
Protein microarray is a powerful technology for both basic research and clinical study. However, because there is no database specifically tailored for protein microarray, the majority of the valuable original protein microarray data is still not publically accessible. To address this issue, we constructed Protein Microarray Database (PMD), which is(More)
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