Junhao Zhang

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In this paper, a novel and robust tracking method based on efficient manifold ranking is proposed. For tracking, tracked results are taken as labeled nodes while candidate samples are taken as unlabeled nodes. The goal of tracking is to search the unlabeled sample that is the most relevant to the existing labeled nodes. Therefore, visual tracking is(More)
In this paper, a novel and robust tracking method based on efficient manifold ranking is proposed. For tracking, tracked results are taken as labeled nodes while candidate samples are taken as unlabeled nodes, and the goal of tracking is to search the unlabeled sample that is the most relevant with existing labeled nodes by manifold ranking algorithm.(More)
Harmonic estimation is an important topic in power system signal processing. Windowed interpolation fast Fourier transformation (WIFFT) is an efficient algorithm for power system harmonic estimation, which can eliminate the errors caused by spectral leakage and picket fence effect. However, the fitting polynomial in the interpolation procedure contains both(More)
The problem of community detection receives great attention in recent years. Many methods have been proposed to discover communities in networks. In this paper, we propose a Gaussian stochastic blockmodel that uses Gaussian distributions to fit weight of edges in networks for non-overlapping community detection. The maximum likelihood estimate of this model(More)
Multiple user decision making is important in today's location-based service scenarios. Existing query services such as kNN and Skyline queries only consider single user and do not consider user's preferences. In this paper, we introduce a novel query type called multiple user-defined spatial queries (MUSQ), which return the best answers for a group of(More)
Ontologies are powerful to support semantic based applications and intelligent systems. While ontology learning are challenging due to its bottleneck in handcrafting structured knowledge sources and training data. To address this difficulty, many researchers turn to ontology enrichment and population using external knowledge sources such as DBpedia. In this(More)
It is a challenging task to develop an effective and robust visual tracking method due to factors such as pose variation, illumination change, occlusion, and motion blur. In this paper, a novel tracking algorithm based on weighted subspace reconstruction error is proposed. We first compute the discriminative weights by sparse construction error with(More)
While tracking has been developed rapidly with the presentation of efficient algorithms recent years, some problems remain unsolved. Occlusion is a challenge for tracking especially in crowded scenes. In this paper, we address the problem by proposing a robust algorithm based on particle filter with blocks and discriminative model. Discriminative model(More)