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A face detection method is presented based on Davinci platform. This paper adopts Adaboost algorithm to identify face, which is operated on TI TMS320DM6467. The results indicate that the method has good accuracy and quick speed for real time application.
This paper analyzes the advantages and disadvantages of equipment, combat simulation data association rules commonly used in the analysis of discrete algorithms, and it proposed and implemented a discretization algorithm based on attribute importance and incompatible degrees, through theoretical research and analysis of algorithm, and experimental comparison, it proves the correctness and validity...
Process mining is one key technology in PASI, it can extract the relevant knowledge according to the event log information recorded in the information system, then restructure a process instance model and makes all the information track in the event log can meet the process model. In this paper, based on ¦Á algorithm of process mining, we propose the process mining ¦Ã algorithm which can discover...
Sound source localization plays a crucial role in many microphone arrays application, ranging from speech enhancement to human-computer interface in a reverberant noisy environment. The steered response power (SRP) using the phase transform (SRP-PHAT) method is one of the most popular modern localization algorithms. The SRP-based source localizers have been proved robust, however, the methods may...
Learning evaluation is an important part of cyber learning. Research studies aiming to increase the accuracy of performance evaluation in E-learning employ data mining technique. Here we describe a scheme for integrating classification algorithms that have been created by a machine learning method, trained on the real data set. The ensemble classifiers combine these classifiers, decision trees, neural...
In order to compare the classification accuracies and performance differences between traditional and probability-based decision tree classifiers, and come to understand those algorithms, which aim to improve construction efficiency of probability-based decision trees, mentioned in "Decisions Trees for Uncertain Data", this paper tested several algorithms, named AVG, UDT, UDT-BP, UDT-LP,...
This paper firstly introduces the research object and key concept of rough set, the data reduction and classification is one of its core areas, Secondly analyzes the characteristics of rough set and limitations on data reduction, which usually is used jointly with other algorithm, and then introduce the rough set attribute reduction algorithm based on the original genetic algorithm, For the shortage...
Getting network video packets quickly from network traffic is the foundation of network video surveillance and management. For obtaining network video packets immediately from network traffic, this paper presents a fast network video packet classification algorithm. When the network video stream is identified, this algorithm could easily obtain all its following packets from network traffic only by...
Microblog has become exceeding popular, with hundreds of millions of tweets being posted every minute on variety of topics. Most hot event will be retweeted thousands of times in short time, which will help us to trace hot event. This paper focuses on tracing those events by mining the text stream in microblog. Although event detection has long been a research topic, the characteristics of microblog...
Text classification is an important research direction of text mining and the research of Chinese text automatic classification is also becoming a research focus of intelligent classification. Against the particularity of the Chinese text classification, this paper presents a three-dimensional vector space model on the basis of the vector space model to improve the accuracy and efficiency of text...
Pedestrian detection is a major difficulty in the field of object detection. In order to achieve a balance between speed and accuracy, we propose a new framework in pedestrian detection based on HOG-PCA and Gentle AdaBoost. Firstly, each block-based feature of the image is encoded using the histograms of oriented gradients (HOG), then Principal Components Analysis (PCA) is used to reduce the dimensions...
The function of protein is closely correlated with its sub cellular locations. New composed proteins can perform normal biological function only after they are translocated to correct sub cellular locations. In this paper, a new selective ensemble classifiers based on EDA algorithm has been proposed. In the method, pseudo amino acid composition was firstly applied to form the protein feature sets,...
For the feature space of high-dimensional data on text clustering contains many redundant features, even "noise" features. The author proposed a feature space correction method, combine with a supervised feature selection methods and K-means clustering method. By analyzing the significance of the features in the clustering process and selecting the features that have more significance, to...
The main difference of the associative classification algorithms is how to mine frequent item sets, analyze the rules exported and use for classification. This paper presents an associative classification algorithm based on Trie-tree that named CARPT, which remove the frequent items that cannot generate frequent rules directly by adding the count of class labels. And we compress the storage of database...
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