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In many computer vision systems, one object can be described by multi-view data. Compared with individual view, multi-view data can contain complete and complementary information of the problem. But when views capture information which is uniquely but not complete enough to give an uniform learning performance, multi-view data may degrade the learning performance and it is therefore not an ideal solution...
Due to the random and uncertain characteristic of networked induced factors, the performance of networked control systems is seriously affected, which is not merely degraded but also cause system instability. In this paper, a newly enhanced control scheme with an improved smith predictor is proposed to solve the issues caused by the complex and uncertain network conditions. A database is integrated...
High dimension of the features employed for face recognition is the main reason to slow down the recognition speed. Additionally, selecting salient facial features has significant impact on the efficiency of face recognition. In order to get the sparse and salient facial features, this paper propose a new sparse learning approach for salient facial feature description. This approach is to learn the...
The classical local binary pattern (LBP) method for facial feature description leads to a high feature dimensionality which requires expensive computational cost for face recognition and ignores the difference of contributions by different features in the same region. In this paper, we propose a structured sparse learning approach for efficient facial feature description. Firstly, a structured sparse...
Aimed to solve the efficiency and timeliness problems in the traditional road updating method, the authors propose a new solution based on floating car data. By the procedures of map matching, point density analysis and automatic vectorization, the authors successfully extract plenty of new roads. The validation result shows that the method proposed here is a more efficient and timely way to update...
DICOM standard is an indispensable component ofPACS, but due to non-DICOM images can be fast loaded and portable with compression, many non-DICOM medical imaging equipments are still widely used in the hospital system, which has led to existence of many non-DICOM medical images. However, the non-DICOM images are unsuitable for doctors to diagnose and study. In this paper, a low-load architecture is...
The paper points out problems in some existing themes,and puts forward a new method for predicting the mobile path based on pattern mining and matching, called PMM.The paper compares the performance of the PMM with Order-k Markov predictors using a trace of the mobility patterns of 1,200 users on real Wi-Fi wireless network.And the result shows that this method can achieve a relatively perfect predicting...
MBBNTree algorithm, which integrates the advantage of Markov blanket Bayesian networks (MBBN) and decision tree, would behave better performance than other Bayesian networks for classification. But the available training samples with actual classes are not enough for building MBBNTree classifier in practice. Active learning aims at reducing the number of training examples to be labeled by automatically...
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