In this paper, we employ the centering theory in pronoun resolution from the semantic perspective. First, diverse semantic role features with regard to different predicates in a sentence are explored. Moreover, given ...
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With the development of agricultural space-Time localisation, sensor network and cloud computing, the amount of agricultural data is increasing rapidly and the data structure becomes more complicated and changeable. C...
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Negative and uncertain expressions widely exist in natural language. Negation and uncertainty identification has become an important task in computational linguistics community. Lacking of corpus hinders the developme...
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A rule-based approach for Chinese zero anaphor detection is proposed. Given a parse tree, the smallest IP sub-tree covering the current predicate is captured. Based on this IP sub-tree, some rules are proposed for det...
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According to Shanno's information theory,the directional feature of texture is defined as the value of directional variable when an image signal attains a singularity of random *** terms of this definition,we calc...
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According to Shanno's information theory,the directional feature of texture is defined as the value of directional variable when an image signal attains a singularity of random *** terms of this definition,we calculate the texture's directional features using Tamura's method and study the directional probability distribution of Contourlet *** we find that the directional features tend to be conveyed across parent and child *** on this conclusion,we establish a novel probability distribution model of hidden direction variables under the condition of hidden state variable's distribution,named Contourlet HMT model with directional *** structure and training method of the model are presented as ***,an unsupervised context-based image segmentation algorithm is proposed on the basis of the proposed *** effectiveness is verified via extensive experiments carried out on several synthesized images and remote sensing images.
Manifold learning has attracted more and more attention in machine learning for past decades. Unsupervised Large Graph Embedding (ULGE), which performs well on the large-scale data, has been proposed for manifold lear...
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In recent years, cloud computing has emerged as an enabling technology, in which virtual machine migration and dynamic resource allocation is one of the hot issues. During the migration of virtual machine, access requ...
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In order to obtain the stable background of a traffic surveillance video, the application scenarios, computational complexity, and results of the Gaussian background model were analyzed. In the background modeling pro...
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Ant colony optimization (ACO for short) has been proved a successful meta-heuristic by a huge of empirical studies. This paper discusses the termination criteria of ACO and therefore provides research ideas to other m...
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Purpose:As to January 11,2021,coronavirus disease(COVID-19)has caused more than 2 million deaths *** diagnostic methods of COVID-19 are:(i)nucleic acid *** method requires high requirements on the sample testing *** c...
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Purpose:As to January 11,2021,coronavirus disease(COVID-19)has caused more than 2 million deaths *** diagnostic methods of COVID-19 are:(i)nucleic acid *** method requires high requirements on the sample testing *** collecting samples,staff are in a susceptible environment,which increases the risk of infection.(ii)chest computed *** cost of it is high and some radiation in the scan process.(iii)chest X-ray *** has the advantages of fast imaging,higher spatial recognition than chest computed ***,our team chose the chest X-ray images as the experimental dataset in this ***:We proposed a novel framework—BEVGG and three methods(BEVGGC-I,BEVGGC-II,and BEVGGC-III)to diagnose COVID-19 via chest X-ray ***,we used biogeography-based optimization to optimize the values of hyperparameters of the convolutional neural ***:The experimental results show that the OA of our proposed three methods are 97.65%±0.65%,94.49%±0.22%and 94.81%±0.52%.BEVGGC-I has the best performance of all ***:The OA of BEVGGC-I is 9.59%±1.04%higher than that of state-of-the-art methods.
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