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Recently, with the obvious increasing number of cardiovascular disease, the automatic classification research of Electrocardiogram signals (ECG) has been playing a significantly important part in the clinical diagnosis of cardiovascular disease. In this paper, a 1D convolution neural network (CNN) based method is proposed to classify ECG signals. The proposed CNN model consists of five layers in addition...
Applying in Factor Analysis and Analytic Hierarchy Process, this study extracted six typical kansei features of Jun Porcelain and found out the relationship between kansei features and Jun's design elements. What's more, this study tried to transfer the kansei features of Jun Porcelain to some redesigned graphic patterns by using Jun's design elements cross-dimensionally. The graphic patterns can...
Urban vegetation, particularly trees, plays important roles in the urban ecosystems. In this study, we examined the potential of WorldView-2 imagery (acquired on September 14, 2012) for urban tree species classification in the capital city of Beijing, China. Four tree species including Chinese white poplar(Populus tomentosa Carrière),Chineses scholartree(Sophora Japonica), Gingko(Ginkgo biloba L.)and...
At present, computer graphics is widely used in various aspects in our daily life. Hence the course is becoming more and more essential, while many students don't know how to study this course, their interests are lost because of awful grades. So how to learn computer graphics is essential now. This paper introduces a method, which is a progressive method on studying and practicing of computer graphics.
Although researches on network traffic identification have already got some achievements, but most of them are not suitable for online traffic classification by considered the dynamic feature of flows. In this paper, we propose a dynamic online traffic identification method by introducing density-based clustering algorithm for stream data called DStream, and using the feature select algorithm to reduce...
The increasing volume of spam has become a serious threat not only to the Internet, but also to the society. However, it's a great challenge to discover the spam from the Internet effectively and efficiently. Content-based filtering is one of the mainstream methods to solve the problem. This paper proposed a content based spam topic detection strategy through keyword extraction. In particular, spam...
Video text contains abundant high-level semantic information, which is important to video analysis, indexing and retrieval. In this paper, fuzzy support vector machine (FSVM) is applied to distinguish background and text in a video sequence. Firstly, the video frame is divided into 8×8 blocks, and we extract the gray, edge and texture feature information as the training samples. Then FSVM is used...
In this paper, BP neural network is applied to fault pattern recognition of pipeline leakage. When the pipeline pressure falls suddenly, the pressure sensors on both sides of the pipeline get pressure signals. The fundamental principal of using wavelet transform to decompose the pressure signal is introduced, using wavelet transform in pressure de-noising and pipeline feature vector extraction, and...
This paper proposes a novel point pattern matching algorithm. Compared with most published works, the proposed algorithm is characterized by its outstanding real time performance, making it the only applicable algorithm for object tracking among the existing ones. Evolved with the definition of point pattern matching, analyzing the object tracking task, it presents a specific description of the novel...
A novel spam filtering algorithm based on 2v-SVM is proposed on the basis of researching of existing spam filtering algorithms in the paper. 2v-SVM can address the difficulties that arise when the class frequencies in training data do not accurately reflect the true prior probabilities of the classes, which is more superiority than standard SVM. Experiment results show that this method can effectively...
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