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Convolutional neural network (CNN) based trackers have achieved significant performances in tracking recently. Most existing CNN-based trackers regard tracking as a classification or similarity searching problem. The two methods have their respective superiorities and limitations because of different supervised objectives. In this paper, we propose a multi-task CNN for visual tracking, not only fully...
In this paper, a novel classifier for classification problems, based on increment support vector data description, is proposed. The proposed method is the expand version of increment support vector data description by bring in two classes of sample. Because of the addition of two kinds of sample. This method can reflect the target sample distribution state more complete in super ball space. The results...
A novel machine learning algorithm named pruning support vector data description (PSVDD) is developed to classify the FFT-magnitude feature of complex high-resolution range profile (HRRP), motivated by the problem of radar automatic target recognition (RATR). The PSVDD algorithm not only inherits the advantage of LSSVM model, which owns low computational complexity with linear equality constraints...
The same as in traditional surgery, surgeons in telerobotic surgery need extensive training to achieve experience and highly accurate instrument manipulation. Traditional training methods like practice in operating room have major drawbacks such as high risk and limited opportunity for which virtual reality (VR) and computer technologies can offer solutions. To accelerate the data transmission speed...
The initial steam pressure is one of the most important parameters affecting the heat rate of supercritical steam turbine. In this paper an approach for the optimization of the initial steam pressure is proposed. Firstly, the real-time data sets acquiring from process control system are processed as training data sets. Then, the characteristic functions for the relationship of unit load, initial steam...
Artificial neural network (ANN) is an important part of artificial intelligence, it has been widely used in remote sensing classification research field. Wetlands remote sensing classification based on ANN is difficult, because of the complex feature of wetlands areas. The purity of training samples for remote sensing image supervised classification is difficult to guarantee that will affect the classification...
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