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Bayesian network is a probability, which is based on a probabilistic inference network of graphical and Bayesian formula is the basis of the probability of network. The paper analyzes general Semantic pixel naming and the implementation process and concept of Bayesian per pixel segmentation (BPPS). On this basis, author presents a novel deep learning framework for clustering and information mining...
Information retrieval deals with organizing data in a structured form and providing a collection of documents as a response to a query of a user. Boolean model, the simplest model is designed to respect exact matching of the query in retrieving the documents. Vector Space model, a popular model permits approximate matches and also provides the documents in a ranked manner. In this tutorial, it is...
Searching for relevant documents in large sets of documents is one of the key tasks in the areas of semantic web and knowledge technologies. This paper deals with analysis and design of improvement for information retrieval (IR) using specific conceptual model automatically created from semantically non-annotated set of text documents. This conceptual model combines locally applied Formal Concept...
This paper proposes a new mesh simplification algorithm which makes effort in reducing the approximation error and improving the mesh regularity of simplified mesh at the same time. In previous mesh simplification researches, algorithms generally focused on the appearance error between the simplified mesh and the original mesh. However, a so-called high quality simplified mesh must have low approximation...
In the fiber image analysis system, correctly segmenting fiber from fiber micrograph is critical for fiber feature extraction and further identification. In this paper, the GVF snake model with the initial contour obtained by contour tracking method based on K-means clustering segmentation is proposed for fiber segmentation. Firstly, the K-means clustering method is used to obtain the initial coarse...
For linear plants, IMC have been shown good robustness properties against disturbances and model mismatches. However, when uncertain processes are concerned, the original IMC structure cannot be directly used for control system implementation. In this paper, an internal multiple model control (IMMC) based on linear model's library is introduced. This approach supposes the definition of a set of local...
In this paper, we propose a new segmentation algorithm that combines a graph-based shape model with image cues based on boosted features. The landmark-based shape model encodes prior constraints through the normalized Euclidean distances between pairs of control points, alleviating the need of a large database for the training. Moreover, the graph topology is deduced from the dataset using manifold...
In this paper a clustering algorithm has been presented for data sets having faces with large variations in pose. Disjoint clusters are created from low-dimensional subspaces of the data set. Partitioning is carried out in the form of a tree-like structure. The subspace-based linear recognition algorithm, Subclass Linear Discriminant Analysis (SLDA) has been employed for recognizing the faces. The...
In current distributed systems, such as Grids, Clouds, or P2P systems, the amount of information to handle influences the way the system is managed. In P2P systems containing large quantities of data, or in Grid systems containing a large number of (often heterogeneous) resources, information about data or resources must be spread through the system in an efficient way in order to allow them to be...
An application in modeling a non-lineal system between temperature, humidity and urban airborne air pollution is presented. In this contribution, the implementation of cluster estimation method as a basis of a fuzzy model identification algorithm has been developed. Fuzzy clustering allowed partitioning this complex non-linear system into many linear sub-systems. Finally, comparison of the performance...
Hand segmentation is often the first step in applications such as gesture recognition, hand tracking and recognition. We propose a new technique for hand segmentation of color images using adaptive skin color model. Our method captures pixel values of a person's hand and converts them into YCbCr color space. The technique will then map the CbCr color space to CbCr plane to construct a clustered region...
Many high-end computing systems use an extremely large number of power-hungry commercial components to achieve high performance. Power reduction and energy conservation are important in these systems for the reason of minimizing operating cost. Two main mechanisms are commonly applied to power reduction in these systems: Dynamic Voltage/ Frequency Scaling (DV/FS) and server number controlling: Vary-On...
A number of recent studies on social networks are based on characteristics which include assortative mixing, high clustering, short average path lengths, broad degree distributions and the existence of community structure. Here, a model which satisfies all the above characteristics is developed. In addition, this model facilitates interaction between different communities. This model gives very high...
Data streams are one of the most challenging environments for machine learning. In many applications, the high volume data streams have an inherent concept drift over time. Identifying novel classes and detecting the occurrence of concept drift in such an environment is a major challenge. In this paper, a new method has been proposed to detect novelty and handle concept drift with limited required...
In this paper, we propose a simple and effective method for human detection based on region growing to improve background subtraction. In some complex scenes, a person will be detected more than one contour region in such cases as that the colors of person clothes are close to the background color so that the original background subtraction cannot obtain good performance. We use region growing method...
Combining extension engineering method with cluster analysis, the classic and limited matter elements were constructed according to air quality standards and main air affecting factors. The logical domain was extended from (0, 1)to (-∞ ,+∞), meanwhile, the quantitative analysis in the classic matter-set which only judged by Yes or No was extended to qualitative analysis, which could show the administrative...
This paper presents concepts, ecosystem, research challenges and directions of Social Services Computing. Social Services Computing is an emerging computing paradigm which sweeps through Social Computing, Internet of Things, Services Computing, and Cloud Computing. Physical things, computer systems and social individuals are connected together through dedicate and complex communication and control...
An important class of community-based activities of mobile users is searching and querying for common locations to visit or come together for a specific task. For this purpose, Group Nearest-Neighbor (GNN) queries are used a generalization of nearest-neighbor queries where the goal is to find one or more points from a set of destination points that have the smallest total distance from all query points...
In the framework of Fuzzy Cognitive maps theory, we propose a novel classify algorithm, which is totally different from the traditional classify algorithm. The novel classify algorithm has three main advantages: Firstly, the procedures of the proposed algorithm are more transparent and understandable, and the classify results have shown the relationship between attributes. Secondly, the predefined...
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