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This paper proposes a fast algorithm based on depth map segmentation for the depth coding of 3D video coding to reduce the coding complexity of the depth map. The proposed algorithm segments the depth map into different regions by modifying automatic thresholding technique. We also propose the search range adjustment according to the classification of the coding tree unit (CTU). The early termination...
With the increasing usage of Wi-Fi infrastructure, methods of indoor localization by Wi-Fi are receiving more and more research efforts in the past. Reducing computational complexity and improving the rate of matching effectively can improve accuracy and real-time of localization. In this paper, we propose a novel clustering approach-AP similarity clustering and K-Weighted Nearest Node (KWNN) method...
Active Shape Model (ASM) is considered as a high level image processing algorithm. Typical applications include image segmentation and interpretation. A major challenge in ASMs is to repeatedly move model points towards true boundaries. It is a crucial step in the algorithm which fails in cases of low contrast images. In this paper, we present a new search algorithm for ASM to tackle segmentation...
With the advent of the information age, various kinds of information have been spread on the Internet. The amount of junk information affects people's lives seriously. In order to filter the harmful Web pages efficiently and effectively, we have suggested a novel text classification algorithm based on Vector Space Model in this paper. This algorithm has adopted the modularized processing mode to deal...
According to label image characteristic, the pressed protuberant characters segmentation method is proposed based on shape index. The pressed protuberant characters and the print character image is withdraws with the morphology processing. obtains the surface gradient is gathered through the shape from shading method, then obtains the shape index operator, and realizes the classification by this as...
Feather selection is a process that extracts a number of feature subsets which are the most representative of the original meaning from original feature set. It greatly reduces the text processing time and increases the accuracy because of removing some data outliers. With the rapid development of Web 2.0 and the further evolution of the Internet, short text like micro-blog plays an important role...
This paper presents an algorithm for obstacle classification and lane line identification using the laser range finder (LRF) sensors, which is used to warn the driver to watch the situation of environment when the obstacle appear in the front. The classification of detecting objects is essential to reduce the danger in traffic. Nevertheless, there may be a noise (or road surface) in far distance....
Protein-RNA interactions are vitally important to a number of fundamental cellular processes, including regulation of gene expression such as RNA splicing, transport and translation, protein synthesis and assembly of ribosome. More detailed information on the Protein-RNA interaction is helpful for comprehending the function notation and molecular regulatory mechanism, meanwhile, knowing the knowledge...
In this paper, an improved Differential Evolution algorithm (ACDE-O) with cluster number oscillation for automatic crisp clustering has been presented. The proposed algorithm needs no prior knowledge of the number of clusters of the data. Rather, it finds the optimal number of clusters on the processing with stable and fast convergence, cluster number oscillation mechanism will search more possible...
In this paper, we propose a new method to detect liver tumors in CT images automatically. The proposed method is composed of two steps. In the first step, tumor candidates are extracted by EM/MPM algorithm; which is used to cluster liver tissue. To cluster a dataset, EM/MPM algorithm exploits both intensity of voxels and labels of the neighboring voxels. It increases the accuracy of detection, with...
Recently, scene recognition is becoming an additional function in digital camera. Automatic scene understanding is a highest-level operation in computer vision, and it is a very difficult and largely unsolved problem. The conventional methods usually use global features (such as color histogram, texture, edge) for image representation and recognize scene types with some classifiers (such as Bayesian,...
Recently ontologies are playing very important part in many areas, such as intelligent information retrieve, knowledge management and organization, electronic commerce and so on, however, several drawbacks must be overcome before ontologies become useful and practical tools. As the number of ontologies are made publicly available and accessible on the web increases steadily, a single ontology is no...
In this paper, a new feature selection method with applications to handwritten digit recognition is proposed. This method is based on recursive feature elimination (RFE) in least squares support vector machines (LS-SVM). Digit recognition is achieved by one-against-all LS-SVMs. The RFE method is adapted to multi-class classification in two ways. One is to prune features for each binary LS-SVM classifier...
The goal of active learning is to select the most informative examples for manual labeling in order to reduce the effort involved in acquiring labeled examples, which is very important for large-scale text classification. However, most of the previous studies in active learning have focused on selecting a single unlabeled example at a time which could be inefficient since the model has to be retrained...
As a complementary mode to synthetic aperture radar (SAR), high range resolution (HRR) is mainly developed to identify moving ground targets automatically. Previous studies have demonstrated many promising solutions in HRR Automatic Target Recognition (ATR). Most of them popularly build on template-based approach and employ mean square error (MSE) metric in matching algorithm to measure the likelihood...
Duplicated web pages responded by search engines not only waste valuable storage, but also aggravate burdens of userspsila browse. Web page de-duplication can effectively improve the information retrieval. This paper proposes pretreatment of web pages to improve the effectiveness and efficiency of web page de-duplication based on feature code according to the principle of data clearing. This paper...
The decision trees and their variants recently have been proposed. All trees used are fixed M-ary tree-structured, such that the training samples in each node must be artificially divided into a fixed number of branches. This study proposes a fuzzy variable-branch decision tree (FVBDT) based on the fuzzy genetic algorithm (FGA). The FGA automatically searches for the proper number of branches of each...
It is very difficult for blind and visually-impaired people getting information from the outside world. In this paper, we propose an adaptive Web news recommendation system named EagleRadio, designed for blind man and supports pervasive access using terminals. EagleRadio offers natural and user-friendly interface. News stories from different topics are read via a speech synthesizer to users and they...
EM (expectation-maximization) algorithm is a classical method for parameter estimation of HMM (Hidden Markov model ). Concerning that EM algorithm is easily affected by initial parameter values, we proposed a mixture splitting algorithm based on decision boundary confusion (DBC) to describe more about boundary distribution. The algorithm mainly includes three aspects: firstly the number of incremented...
The natural immune system is a robust and powerful information process system that demonstrates features such as distributed control, parallel processing and adaptation. Artificial immune systems (AIS) are machine-learning algorithms that embody some of the principles and attempt to take advantages of the benefits of natural immune systems for use in tackling complex problem domains. Using the artificial...
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