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Grey Wolf Optimizer (GWO) is a new meta-heuristic optimization. It is inspired by the unique predator strategy and organization system of grey wolves. Since the GWO algorithm is easy to fall into local optimum especially when it is used in the high-dimensional data, an improved GWO algorithm combined with Cuckoo Search (CS) is proposed in this paper. By introducing the global-search ability of CS...
Cross domain data such as numerical or categorical types are ubiquitous in practical network. Network anomaly detection based on cluster analysis exist some difficulties, for example, the initial center of cluster analysis is sensitive and easy to fall into the local optimal solution. Cross domain data involved great information, but can't be effectively used, which will influence the performance...
In this paper, real-time recognition and tracking of multiple similar targets at 6-DOF motion is studied. A real-time multi-target recognition algorithm is proposed and implemented based on Marker to solve the difficult problem of distinguishing multiple similar targets. Because the lighting conditions of markers at 6-DOF motion are widely changeable, existing marker recognition algorithms are sensitive...
Software has been changing during its whole life cycle. Therefore, identification of source code changes becomes a key issue in software evolution analysis. However, few current change analysis research focus on dynamic language software. In this paper, we pay attention to the fine-grained source code changes of Python software. We implement an automatic tool named PyCT to extract 77 kinds of fine-grained...
Time series is a ubiquitous data existed in different domains including finance, medicine, business and other industrial fields. Recently, time series data mining attracts much attention. In this paper, we propose multilayer piecewise aggregate approximation (MPA) to measure the Similarity of time series. The proposed method is constituted of two parts: multi-level segment method based on extreme...
In order to enhance efficiency and accuracy of dynamic hand gesture recognition based on HMM method. we propose a new HMM algorithm combined with the DTW for the computation's high complexity of HMM method in the training stage. The new HMM can establish the relationship of fuzzy closeness degree between the DTW algorithm and the HMM algorithm. Meanwhile, it can combine with the template adaptive...
Anomaly detection technique play an extraordinary role in the Intrusion Detection System (IDS) for its ability to detect novel attacks. To overcome the high-dimensionality problem the anomaly detection cursed of, we propose a novel Meta-Heuristic-based Sequential Forward Selection (MH_SFS) feature selection algorithm, which can be generally implemented in anomaly detection system. It is an improvement...
Extracting opinion words and opinion targets from online reviews is an important task for fine-grained opinion mining. Usually, traditional extraction methods under the pipeline-based framework have higher precision but lower recall, while methods in the propagation-based framework possess greater recall but poorer precision. To achieve better performance both in precision and recall, this paper proposes...
Topic evolution is an important research topic in natural language processing. Existing work has been focused on topic evolution of long text such as Web pages, news and blogs. In this paper, we aim to derive topic evolution summaries and its topology structures from short text like microblogs. We propose a microblog topic evolution algorithm based on retweeting relationships (MTERR). Firstly, we...
In security surveillance video (SSV), foreign object occlusion is increasingly common. Automatic detection of suspicious occlusion has become important. In this paper, a banner occlusion detection approach is proposed. The proposed approach first detects the banner in the image using both color feature and shape feature. More specifically, the proposed approach exploits the HSV color space to extract...
In the dynamic social network, how to use data mining tools to find the hidden dynamic knowledge in the social network has become the focus of the study. It can be applied to a wide range of areas with good practical value and application significance. We propose a novel algorithm called iDBMM based on the improvement of DBMM algorithm. At first, iDBMM algorithm classifies the training set to obtain...
In a typical computer vision application, such as video event detection, the “meaningful” information is fundamentally represented by pre-defined features, which determine the appropriate analytical methodologies in the following processing phases. Based on the uncompressed low-level image characteristics, such as colour, intensity and spatial positions, the features used for event detection in this...
In this paper, gesture recognition algorithm with kinect sensor is proposed. the depth cue is used to locate the hand area. Based on the histograms of oriented gradient (HOG) and adaboost learning methods, the static hand algorithm is designed to recognize the predefine gesture in the hand Area. by tracking the hand trajectory by kinect, hmms is used to train and classify dynamic gesture. an intelligent...
Modelling events in densely crowded environments remains challenging, due to the diversity of events and the noise in the scene. We propose a novel approach for anomalous event detection in crowded scenes using dynamic textures described by the Local Binary Patterns from Three Orthogonal Planes (LBP-TOP) descriptor. The scene is divided into spatio-temporal patches where LBP-TOP based dynamic textures...
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...
According to the off-line handwritten Chinese characters, a classification and recognition method which is combined by pruning FSVM coarse classification and SVM fine classification is proposed in this text. First cut no value minor to reduce the number of support vector machines, and then determine the coarse classification through fuzzy membership when the coarse classification is done. In fine...
Because of a large number of micro-blog's junk posts, how to instantly browse hot topics in micro-blog is faced with severe challenges. We propose a new extraction algorithm of hot topics to remove the false hot topics. The algorithm sets a group of parameters what is a determine condition. Parameters contain word frequency, users' number, occurrence number, users' discrete degrees, and time distribution...
This paper presents a dual watermarking scheme of digital images based on the dynamic feature points. In our dynamic feature watermarking scheme, the watermrking energy distributes on the dynamic feature set extracted by the key-decided orthogonal vector operator, and a dual watermark that is formed embeding copyright watermark into another child watermark consisting of features selected from the...
The emotion tendency of sentiment word is divided into two types: static emotion tendency and dynamic emotion tendency. Basic semantic lexicon is static emotion tendency, in the real context, but it is different between static emotion tendency and dynamic emotion tendency. The paper proposes a method based on degree lexicon, negative lexicon and dependence relationship of sentence elements. The experimental...
The gridding is an essential task for DNA microarray image analysis which will definitely affect the spot segmentation and intensity extraction. The accuracy and reliability of existing gridding methods depend on the artificial experience value owing to they can not dynamically determine the required processing parameters. In this paper, the gridding problem is turned into an optimizing problem by...
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