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Visual tracking is intrinsically a temporal problem. Discriminative Correlation Filters (DCF) have demonstrated excellent performance for high-speed generic visual object tracking. Built upon their seminal work, there has been a plethora of recent improvements relying on convolutional neural network (CNN) pretrained on ImageNet as a feature extractor for visual tracking. However, most of their works...
Chromatography has been widely used in discrimination and quality control for Chinese medicines (CMs). Nevertheless, regular analytical approaches are not applicable if training samples are small while features are large. Support vector machine (SVM) with recursive feature elimination algorithm (RFE-SVM) is presented in this study for discrimination of Pericarpium Citri Reticulatae through small chromatographic...
Electrode shift of a prosthetic device is one of most challengeable problems in surface Electromyography (sEMG) based hand gesture recognition. Electrode shift is usually caused by repositioning, donning or doffing of a prosthetic device. Accuracy of gesture recognition may significantly drop since a pattern of collected signals may change after electrode shift. Although re-training a recognition...
The switchgear, which is directly oriented the needs of the distribution network and the users, is an important kind of facilities whose operation condition is straight relevant to the quality and reliability of power supply. In contrast to the traditional routine maintenance or break maintenance, the condition based maintenance has been developed rapidly recent years as an advanced method, where...
Defect number prediction is essential to make a key decision on when to stop testing. For more applicable and accurate prediction, we propose an ensemble prediction model based on stacked generalization (PMoSG), and use it to predict the number of defects detected by third-party black-box testing. Taking the characteristics of black-box defects and causal relationships among factors which influence...
PurposesThe application of FESTO training system in the design of automatic control system is introduced. With the help of resarch of one example, the real industrial application of the conveying controlled automatically, one convenient design method of pneumatic electrical - pneumatic automatic control system is developed Procedures. Practice proves that using this method is a good way for learning...
BP neural network model is advanced in this paper for the analysis of dam deformation monitoring data, aiming at the limitation of traditional method of statistical model. Structure and algorithm of BP neural network model is introduced, together with the normalization of sample data. The application of this model to Taihe Reservoir Dam shows that its precision is prior to that of statistical model.
Support vector machine has been widely used in the classification issues. This paper proposed a new cascade support vector machine classification algorithm CSVM with AdaBoost algorithm framework and support vector machine SVM combination to deal with the problem of multiple classifiers. for the problem of consuming time in the multi-classification problems with support vector machines, this paper...
Following the intuition that the image variation of faces can be effectively modeled by low dimensional linear spaces, we propose a novel linear subspace learning method for face analysis in the framework of graph embedding model, called semi-supervised graph embedding (SGE). This algorithm builds an adjacency graph which can best respect the geometry structure inferred from the must-link pairwise...
Subspace methods have been successfully applied to face recognition tasks. It is well-studied in both unsupervised learning and supervised learning, such as Eigenface and Fisherface. In practice, besides abundant unlabeled examples, domain knowledge in the form of pairwise constraints is commonly available, which specifies whether a pair of instances belong to the same class or different classes....
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