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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Xu, Bei Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)9780769547947

This paper proposes a method which is not for summarization but for extracting multiple facets from a text according to the keyword sets representing readers' interests, so that readers can obtain the interested facets and carry out faceted navigation on text. A facet is a meaningful combination of the subsets of the text. Previous text process technologies are mostly based on text features such as word frequency, sentence location, syntax analysis and discourse analysis. These approaches neglect the cognition process of human reading. The proposed method considers human reading process. Experiments show that the facet extraction is effective and robust. © 2012 IEEE.

关键词： Navigation

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Dual-Graph Regularized Sparse Low-Rank Matrix Recovery for Tag Refinement 14th

Dual-Graph Regularized Sparse Low-Rank Matrix Recovery for T...

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14th International Conference on Bio-inspired computing: Theories and Applications, BIC-TA 2019

作者： Sun, Dengdi Bao, Yuanyuan Ge, Meiling Ding, Zhuanlian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230601 China School of Internet Anhui University Hefei230039 China

ISBN: (纸本)9789811534140

In recent years, extremely large amounts of images with manual tags are easily available in many social websites such as Twitter, Flickr, and Instagram. However, these user-provided tags are often imprecise and incomplete, which inevitably limits the performances of image retrieval and other related applications. To this end, tag refitment technology aims at improving the quality of images tags automatically, and has been a fundamental challenge in Internet era. In this paper, we propose a novel dual-graph regularized sparse low-rank matrix recovery method, referred to as DGSLR briefly, to infer and improve the manual tags. Specifically, our DGSLR model first suppress the sparse noisy tags by norm, and decompose simultaneously the residual low-rank matrix to learning the low-dimensional vector representations of images and tags. Moreover, the visual similarities and the tag pairwise correlation are fully exploited to smooth the decomposition results by using the dual lapalcian graph regularization terms. For optimization, an improved alternative iteration strategy is designed to solve the resulting objective function. Extensive experiments on the tasks of tag refinement demonstrate the superior performance of the proposed algorithms over several representative methods, especially when the manual tag data is highly noisy and sparse. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Conditional Generative Adversarial Defogging Algorithm Based on Polarization Characteristics 33

Conditional Generative Adversarial Defogging Algorithm Based...

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第33届中国控制与决策会议

作者： Jingjing Zhang Kangsheng Bao Xin Zhang Fudong Nian Teng Li Yuzhou Zeng Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education (Anhui university) Key Laboratory of Polarized Light Imaging and Detection Technology in Anhui Province Hefei No.6 High School Hefei University

ISBN: (纸本)9781665431293

To overcome image degradation under the conditions of haze,and fog,a method using conditional generative adversarial defogging algorithm based on polarization characteristic is *** original images with different polarization angles were obtained from the original image,and then the polarization images were characterized using Stokes *** the relationship between Stokes vector and polarization image,each polarization image with different angles is input into the same network to extract *** the same time,the enhanced network is used to extract the characteristics of the fog area in the polarization image,and the polarization information is extracted by layer jump connection,which is fused with the image features of different *** constructing the loss function and obtaining the optimal solution,the fog-free image is finally *** results show that a clear image can be reconstructed in fog situations by using conditional generative adversarial network-based on polarization characteristics,and the structural similarity is improved by about 10%,the peak signal to noise ratio is increased by about 0.5.

关键词： polarization characteristics conditional generative adversarial network image processing image defogging feature fusion enhanced network

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On Isodual Double Toeplitz Codes

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Journal of Systems Science & Complexity 2024年第5期37卷 2196-2206页

作者： SHI Minjia XU Li SOLÉ Patrick Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationSchool of Mathematical SciencesAnhui UniversityHefei 230601China State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China CNRS University of Aix MarseilleCentrale MarseilleI2MMarseille 13284France

Double Toeplitz(shortly DT)codes are introduced here as a generalization of double circulant *** authors show that such a code is isodual,hence formally self-dual(FSD).FSD codes form a far-reaching generalization of self-dual codes,the most important class of codes of rate ***-dual DT codes are characterized as double circulant or double ***,even binary DT codes are characterized as double *** examples obtained by exhaustive search show that the codes constructed have best-known minimum distance,up to one unit,amongst formally self-dual codes,and sometimes improve on the known *** q=2,the authors find four improvements on the best-known values of the minimum distance of FSD *** F4 an explicit construction of DT codes,based on quadratic residues in a prime field,performs equally *** authors show that DT codes are asymptotically good over ***,the authors construct DT codes arbitrarily close to the asymptotic Varshamov-Gilbert bound for codes of rate one half.

关键词： Double circulant codes double Toeplitz codes isodual codes formally self-dual codes

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Perfect plane wave injection for symplectic finite-difference time-domain scheme

Perfect plane wave injection for symplectic finite-differenc...

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2012 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2012

作者： Wang, Hui Huang, Zhi-Xiang Wu, Xian-Liang Wu, Bo Shen, Jing Key Lab. of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Department of Physics and Electronic Engineering Hefei Normal University Hefei 230061 China

ISBN: (纸本)9781467321839

In this paper, the method of splitting plane wave finite-difference time-domain (SP-FDTD) algorithm is presented for the initiation of plane wave sources in symplectic finite-difference time-domain (SFDTD) scheme. By splitting the fields on one-dimensional (1D) grid and using the nature of numerical plane wave in FDTD, an efficient plane wave sources is simulated on 1D grid, and a perfect match is achieved for a plane wave propagating at any angle forming an integer grid cell ratio. Numerical examples show the valid of the proposed method. © 2012 IEEE.

关键词： Wave propagation

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Verification algorithm of a sequential circuit's equivalence based on state transfer graph

Verification algorithm of a sequential circuit's equivalence...

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2nd International Symposium on Information Technologies and Applications in Education, ISITAE 2008

作者： Li, Wei Yang, Desheng Lu, Ying Zhang, Yichao Institute of Computer Science and Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9780863419133

An equivalence verification algorithm of sequential circuits [1] based on state transfer graph (STG) is presented in this paper, which obtains some certain useful information through verifying the corresponding state transfer graphs' isomorphism, namely that two corresponding sequential circuits' equivalence . And the verifying includes two steps: firstly, find out all state pairs of the vertexes, which are being verified;secondly verify the equivalence of state pairs, if all the state pairs can be matched as equal state pairs, thus we can come to a conclusion that the corresponding circuits have the same sequential behavior. The algorithm mainly verifies ISCAS85 circuits and some simple state transfer graphs, and the final experiment data shows that the algorithm introduced in the paper will obtain better results compared to BDD(Binary Decision Diagram) and SET(Symbolic Trajectory Evaluation) methods. © 2008 IET.

关键词： Timing circuits

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Face recognition using fuzzy rough set and support vector machine

Face recognition using fuzzy rough set and support vector ma...

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2010 IEEE International Conference on intelligent computing and intelligent Systems, ICIS 2010

作者： Wang, Shi-Yi Tao, Liang MOE Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei Anhui 230039 China Computer Department Chaohu College Chaohu 238000 China

ISBN: (纸本)9781424465835

This paper proposes a method of face recognition using the support vector machine (SVM) based on the fuzzy rough set theory (FRST). Firstly, features from human face images are extracted by combining the 2-D wavelet decomposition technique with the grayscale integral projection technique. And then, the attribute reduction algorithm based on FRST is applied in face recognition. The reduction algorithm based on FRST can eliminate the redundant features of sample dataset and reduce the space dimension of the sample data. The proposed method avoids losing of information caused by dispersing before original rough set attribute reduction. Experimental results show that it can improve the classification accuracy in face recognition as compared with the method using the original rough set. ©2010 IEEE.

关键词： Face recognition

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Research on patent classification based on hierarchical label semantics 3

Research on patent classification based on hierarchical labe...

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3rd International Conference on Education, Knowledge and Information Management, ICEKIM 2022

作者： Chen, Jie Zhao, Shu Lu, Fan Liu, Feng Zhang, Yangping Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing Hefei China Anhui University School of Computer Science and Technology Hefei China

ISBN: (纸本)9781665416665

Patent classification is an essential task in patent information management and knowledge mining. Most existing studies are based on the textual content of individual patent texts (e.g., titles and abstracts) for classification, but the patent also has label information with hierarchical structure and semantic description. However, the semantics correlation of patent texts and their labels have been largely ignored. In this paper, we propose a novel framework called HLSPC for patent classification by leveraging the hierarchical semantics correlation of patent texts and their labels. Specifically, we first apply a patent representation learning module for capturing the semantics representation of patent texts and hierarchical labels. Then, we design a label attention learning module to build the semantics correlation between patent texts and hierarchical labels, which enhances patent representation. Finally, we deploy a multi-level fusion module to get the refined category prediction for each patent which can preserve both local and global hierarchical prediction information. Extensive experimental results on two English patent datasets demonstrate the effective power of the HLSPC model. © 2022 IEEE.

关键词： Semantics

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A novel description of the reproducing kernel support vector machines

A novel description of the reproducing kernel support vector...

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2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011

作者： Xu, Li-Xiang Luo, Bin Yu, Feng-Hai Xie, Jin Department of Mathematics and Physics Hefei University Hefei China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui 230039 China

ISBN: (纸本)9781424487257

Support vector machines (SVMs) and related kernel-based algorithms have become one of the most popular approaches for many machine learning problems. but little is known about the structure of their reproducing kernel Hilbert spaces (RKHS). In this work, based on Mercer's Theorem, the relation among reproducing kernel (RK) and Mercer kernel, and their roles in SVMs are discussed, corresponding to some important theorems and consequences are given. Furthermore, a novel framework of reproducing kernel support vector machines (RKSVM) is proposed. The simulation results are presented to illustrate the feasibility of the proposed method. Choosing a proper Mercer kernel for different tasks is an important factor for studying the result of the SVMs. © 2011 IEEE.

关键词： Support vector machines

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Optimizing Antenna Design through AI Integration: A Concise Review 7

Optimizing Antenna Design through AI Integration: A Concise ...

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7th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Liu, Xiaotian Chung, Kwok L. Li, Wenbiao Li, Ruihong Huang, Shuwei Li, Yingsong Huizhou University School of Computer Science and Engineering Huizhou516007 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China

ISBN: (纸本)9798350384437

The integration of artificial intelligence with antenna design and optimization represents a promising research frontier. This paper provides a concise overview of current research, emphasizing the computational cost challenges associated with implementing machine learning in antenna design and optimization. It explores the advantages and limitations of utilizing the Kriging model and the Surrogate-assisted Differential Evolution Algorithm (SADEA) series to tackle these cost constraints. © 2024 IEEE.

关键词： Smart antennas

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