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A variety of problems are related to real-world gesture recognition, such as continuous data streams, concept drift, novel and outlier samples, noise, scarcity of manually labeled data, on-line classification and the fact that the same gesture may implement in different way. Two important features should be included in the classifier to overcome these problems, which are the ability of detecting the...
One of the most important parts of search engines is the ranking unit. Many different classical ranking algorithms based on content (such as TF-IDF and BM25) and connectivity (such as HITS and PageRank) have been used in web search engines to find pages in response to a user query. Although these algorithms have been developed to improve retrieval results, none of them can take advantage of power...
Next generation sequencing (NGS) technology has increasingly become the backbone of transcriptomics analysis, but sequencer error causes biases in the read counts. In this paper we establish a framework for predicting true sequences from NGS data. We formulate this task as a classification problem. We define several features, such as log likelihood ratio of estimated true counts, error probability...
The rapid development of multimedia related technologies and internet infrastructure have made general users can create, edit, and post their contents and can easily access any content that they desire. But it also leads to the harmful side effects that are creation and uncontrolled distribution of objectionable contents. Especially it is very serious for pornographic contents that are more than about...
Studies of obesity and eating disorders need objective tools of Monitoring of Ingestive Behavior (MIB) that can detect and characterize food intake. In this paper we describe detection of food intake by a Support Vector Machine classifier trained on time history of chews and swallows. The training was performed on data collected from 18 subjects in 72 experiments involving eating and other activities...
Too many unimportant attributes are ended up specifying in medical disease sample data sets if we are not sure which attribute to include for disease prediction, which could spoil the classification and increase many unwanted calculations of the medical disease prediction. Thus how to preprocess these medical data and enhance the prediction performance is worth a problem to research. In the paper,...
This paper describes a proposition for constructing an automatic personalization system based on SVM (support vector machine) method. Our approach helps the learning units designers to select automatically the learning scenarios adapted to learners. In our experimentation, we have used a database that contains information about computer science engineering students of the Tlemcen university and descriptions...
Based on stating the principle of support vector machine (SVM) classifier, this paper analyses the data collected traits by fixed detectors and the traffic characteristics of freeway chiefly. Also, this paper proposes traffic pattern eigenvectors by data of several continuous time intervals for the single traffic parameter, puts forward multiple SVM classifier fusion models and operation flow, as...
Aimed at the problem that many AID algorithms have lower detection rate and higher false alarming rate, a kind of AID algorithm based on multi-SVM classifier is proposed. Also, the framework and flow of this algorithm were designed, and eigenvector constituted by data of the same traffic parameter in some continuous periods was proposed, then the validity and portability were analyzed by simulation...
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