Qianying Wang

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Learning an appropriate distance metric is a critical problem in pattern recognition. This paper addresses the problem in semi-supervised metric learning and proposes a new regular-ized semi-supervised metric learning (RSSML) method using local topology and triplet constraint. Our regularizer is designed and developed based on local topology, which is(More)
Presenting effective augmenting information is helpful for users to perceive and interact in augmented reality systems. In this paper, a novel method for evaluating the human-computer interface in optical see-through augmented reality system is proposed. The main contribution presented in this paper is a user-based study that adopts the Radius Basis(More)
In semi-supervised classification boosting, a similarity measure is demanded in order to measure the distance between samples (both labeled and unlabeled). However, most of the existing methods employed a simple metric, such as Euclid-ian distance, which may not be able to truly reflect the actual similarity/distance. This paper presents a novel similarity(More)
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