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The algorithm of extracting pedestrian features based on Local Binary Pattern (LBP) has the problems of being unable to depict the human visual sensitivity. We proposed an Significant Local Binary Pattern (SLBP) which fused the characteristics of human visual pedestrian system. We extracted the significant factor based on Weber's law, and added the significant factor as a weight to the LBP eigenvalue...
This paper presents a new approach for acoustic environment classification based on the discrete Hartley transform. The approach applies a Hidden Markov Model based classifier on test data composed of audio clips, in order to determine which environment is surrounding these audio clips. The approach uses features obtained from the discrete Hartley transform, leading to a set of features that require...
Millions of comments are available on forums, Facebook, Tweeter, YouTube etc. Proper analysis of these huge comments can lead to solve many social, economic, political, business related questions which otherwise are difficult to understand and analyse. Proposed system explores the statistical approach for sentiment analysis of product reviews using expectation maximization algorithm. Systematic mathematical...
Stack Overflow is one of the most popular question-and-answer sites for programmers. However, there are a great number of duplicate questions that are expected to be detected automatically in a short time. In this paper, we introduce two approaches to improve the detection accuracy: splitting body into different types of data and using word-embedding to treat word ambiguities that are not contained...
In this paper, we propose a phase field variational model with arctangent regularization for saliency detection. The classical Cahn-Hilliard model is used to extract features in complex image domain with highly anisotropic interfacial energy. Various visual attention features can be detected by minimizing the energy functional. The processing of saliency detection can be seen as a dynamical competition...
Depression is considered as a psychosomatic state associated with the soft biometric features. People suffering from depression always behave abnormal. Depression is a clinically proven disorder that can overwhelm a person and his ability to perform even a simple task. Soft biometric provides important information about a person without being enough for their verification because they lack uniqueness...
We propose a novel idea for the preparation of slides automatically from the documents which reduce the time consumption and efforts of the presenter. The proposed method uses Support Vector Regression to predict the importance of the sentences and Integer Linear Programming is used for maximizing the importance of the key phrases. Key phrases are used as subheadings for the sentences. The draft copy...
Extraction algorithm of multi-scale pyramid spatial-Temporal interesting points(STIPs) is widely applied to various vision applications, especially in pedestrian detection. The traditional algorithm's computational cost is too much to save much time, so a new method based on prediction is proposed in this paper. Firstly, put a radio into several groups on the basis of original pyramid. Then calculate...
Due to the influence of both background interference and time-varying position, it is difficult to detect the moving object by computer vision in the complex background environment. This paper novelly builds a topological structure of typical features to detect object. The presented method can effectively detect the object which is scaling, rotating or in affine transformation, because of the using...
Image registration is a process of determining the geometrical transformation that aligns two or more images taken from different viewpoints and sensors at different times. Scale Invariant Feature Transform (SIFT) method has gained more popularity since it extracts the highest number of features and matching points compared to Speeded-Up Robust Feature (SURF) and Harris Corner Detector at little computational...
This paper proposes an efficient islanding detection and classification technique based on the Extreme Learning Machine (ELM) algorithm for the wind farm based distributed generation (DG) connected to a power grid. In regard to design of any classification technique, learning time is a vital aspect to be considered. Thus having inherited with a good capability of generalization and an efficient and...
Object motion tracking has been done for videos with various methodologies. The existing systems are mainly based on single feature and motion detection as a single object by taking the movement of the feature selected. We propose a moving object tracking method that uses low-level features like centroid location of tracked object combined with the color feature. Centroid location of each moving object...
Bag-of-Features (BOF) representation is a very popular model for content based image classification. In BOF, term frequency (tf) and inverse document frequency (idf) is a very popular model to compute the weights of the visual vocabularies. However, tf-idf model does not contain the class information of images. Fortunately, chi-square model contains the class information well. So, in order to enhance...
The vital role Supervisory Control And Data Acquisition (SCADA) systems play in controlling the modern infrastructure; along with the rapid evolution of these systems have turned them into one of the most desired targets for malicious attackers. Moreover, SCADA-specific attacks are becoming more sophisticated, and yet security measures are deployed at a very slow pace. In this work, we present a SCADA-specific...
Brain computer interface technology comes at the beginning of the popular study subject for scientist that of excite all of humanity. By means of that technology it is allowed to control electronic devices for paralyzed or partial paralysis humans to make their lives easier. In literature there have been many cursor movement imagery studies based on electroencephalogram (EEG) signals. However, the...
In this paper, three moment invariants techniques have been used to extract the shape properties of the image. There are geometric moment, zernike moment and united moment invariants. These moment invariants have been used to analyze the image due to its invariant features of an image based on scaling factor and rotation. A set of equations known as intra-class analysis has been applied to measure...
Graphical objects are important elements of freely handwritten notes but their segmentation from the document is challenging due to their irregular properties. This paper introduces an original solution for automatically segmenting diagrams and drawings from unstructured online documents. We propose a multi-scale representation of the document modeled as a hierarchical Conditional Random Field to...
This paper presents an approach to the Chinese Personal Name Disambiguation (PND). The key to clustering is the similarity measure of context, which depends on the features selection and representation and calculation method. First HIT Tongyici Cilin (Extended) is introduced to Chinese PND to enhance the clustering effect. Exploration about more word similarity is also performed to alleviate the data...
Integrated health management (IHM) is an advanced technology which integrated artificial intelligence with advanced test and information technologies. Having gone through fault detection, isolation and reconfiguration and immerged with the state of arts reasoning technologies, IHM monitors and controls the function of critical systems and components in order to ensure safe and efficient operation...
Broadcast news segmentation is a recognised important task in audiovisual archives retrieval systems. Though research is very active in the field, the problem has not been satisfactorily solved yet. This paper presents a promising novel methodology at segmenting news programmes based on a probabilistic approach, and innovative evaluation framework to assess the performance of the proposed techniques...
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