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In cognitive radio network (CRN), secondary users (SUs) suffer from the spectrum sensing data falsification (SSDF) attack launched by malicious users (MUs). To deal with SSDF attack, one of the typical artificial neural networks (ANN): self-organizing map (SOM) neural network is recommended. SOM network possesses the ability of classifying the SUs into categories with different frequency of occurrence...
Recently, machine learning is widely used in applications and cloud services. And as the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems. To give users better experience, high performance implementations of deep learning applications seem very important. As a common means to accelerate algorithms, FPGA has high performance, low power consumption,...
Learning to rank is an important task for many data mining applications. Essentially, the goal of learning to rank is to learn an appropriate similarity or distance metric to determine the relevance relationships among data points. However, most of the existing approaches for distance metric learning are limited in three aspects. First, they often assume a fixed form of distance metric for the entire...
Human silhouette reconstruction has a wide range of applications in motion analysis, object segmentation and tracking, etc. In this paper, we propose a human silhouette reconstruction method based on the exploration of temporal information. Given a test silhouette, the proposed method aims to find its reliable templates for reconstruction by using the intrinsic temporal relationship among different...
The fuzzy neural network technology is one of the hot topics of Data Mining. According to the Max Similarity Rule, this paper sets forth the cross entropy theory with formulae deduction in detail and a new activation function. Compare with the BP algorithm (error back propagation), which based on the error square sum rule and Sigmoid or Hyperbolical function, the classify algorithm based on the cross...
The World Wide Web provides great convenience for users to obtain information. However, there exists much harmful information on the Internet, such as pornographic content and prohibited drugs' information. Thus, how to filter harmful Web pages on the Internet is quite an important issue. In general, the problem of harmful Web page filtering is converted to that of Web page classification, which needs...
Image spam is a new obfuscating method which spammers invented to more effectively bypass conventional text based spam filters. In this paper, a framework for filtering image spams by using the Fourier-Mellin invariant features is described. Fourier-Mellin features are robust for most kinds of image spam variations. A one-class classifier, the support vector data description (SVDD), is exploited to...
With the large number of Web sites promoting the use of illicit drugs, it has become important to screen these sites for the protection of children on the Internet. Conventional keyword-based approaches are not sufficient because these Web sites often have lots of images and little meaningful words than prices. We propose an AdaBoost-based algorithm for cannabis image recognition. This is the first...
Dynamical shape priors are curical for level set-based non- rigid object tracking with noise, occlusions or background clutter. In this paper, we propose a level set tracking framework using dynamical shape priors to capture contours changes of an object in a periodic action sequence. The framework consists of two stages - off-line training and on-line tracking. During the off-line training stage,...
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