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The extant work on network analyses has thus far paid little attention to the heterogeneity in time lags and speed of information propagation along edges. In this paper, we study this novel problem, modeling the time dimension and lags on network edges, in the context of paper and patent citation networks where the variation in the speed of knowledge flows between connected nodes is apparent. We propose...
One of the most important tasks in remote sensing data processing is the production of orthorectified images. Such tasks are computationally intensive and can become a bottleneck for remote sensing image processing, particularly in high-throughput environments, such as large satellite imagery processing centers. This letter explores the use of massive parallel processing graphical processing unit...
We present an effective deformable part model for face detection in the wild. Compared with previous systems on face detection, there are mainly three contributions. The first is an efficient method for calculating histogram of oriented gradients by pre-calculated lookup tables, which only has read and write memory operations and the feature pyramid can be calculated in real-time. The second is a...
Although numerous online learning strategies have beenproposed to handle the appearance variation in visualtracking, the existing methods just perform well in certaincases since they lack effective appearance learning mechanism. In this paper, a joint model tracker (JMT) is presented, which consists of a generative model based on MultipleSubspaces and a discriminative model based on improvedMultiple...
Critical Path Method (CPM) is widely used in construction engineering scheduling. Through calculating Early Start (ES), Early Finish (EF), Late Start (LS), and Late Finish (LF), the duration of a project can be obtained, and critical path can be found. However, in reality, the duration of each activity is uncertain with a distribution, instead of a constant number. Meanwhile, the cost of each activity...
In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor space to 3D tensor space, learned by using statistical learning, is used for the shape recovery. In the learning phase, the two tensor models are constructed for NIR and 3D images respectively, and a canonical correlation analysis...
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