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Objective To investigate the classification ability of quantitative radiomics features extracted on non-contrast-enhanced CT (NECT) image for discrimination of AVM-related hematomas from those caused by other etiologies. Methods Two hundred sixty-one cases with intraparenchymal hematomas underwent baseline CT scan between 2012 and 2017 in our center. Cases were split into a training dataset (n =...
In the audio event classification or detection research field, the representation of the audio itself is important. Many researchers tried to apply Deep Belief Network (DBN) to learn new representations of the audio. The mel filter-bank feature, which is obtained based on mel scale, is commonly used as the low level representation of the audio in the pre-processing procedure of DBN. However, the mel...
Audio event classification plays an important role in surveillance systems. Due to the constrain of short-time Fourier transform (STFT), the extraction of the audio frequency domain features, as the essential work among the audio event classification, still have some difficulty when conducted on a big audio frame. The traditional concatenation method of feature vector for the successive audio windows...
In this paper, new active learning methods are proposed to filter Chinese spam. It is time-consuming and expensive to label the spam emails in the large datasets. Active learning methods can conspicuously reduce labeling cost by identifying informative examples and speed up online Logistic Regression filter. The experiments illustrate that our methods not only decrease the number of label requests,...
This project's purpose is to give some ideas of Completely Automated Turing Test to Tell Computers and Humans Apart(CAPTCHA), an automatically Turing test which tell human and machine apart, vulnerabilities and its state of the art. As you know, CAPTCHAs are popular in network security area and has been lasting for nearly ten years. However, more and more schemes are suffering successful attacks....
A new method to solve the convex hull problem in n-dimensional spaces is proposed in this paper. At each step, a new point is added into the convex hull if the point is judged to be out of the current convex hull by a linear programming model. For the linear separable classification problem, if an instance is regarded as a point of the instances space, the overlap does not still occur between the...
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