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检索条件"机构=Key Lab. of Intelligent Computing and Signal Processing"

共 444 条记录，以下是181-190 订阅

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The Downlink Performance of Massive MIMO Systems under Different Uplink Pilot Allocation Schemes

The Downlink Performance of Massive MIMO Systems under Diffe...

引用

第二届材料科学应用与能源材料国际研讨会

作者： Ziju Huang Hui Zhi Feiyue Wang Key Lab of Computing Intelligent and Signal Processing(Ministry of Education) Anhui University

In the scenario of time division duplexing(TDD) massive multiple-input multiple-output(MIMO) system,when there is pilot contamination(PC) in the uplink,different pilot allocation schemes will affect the results of the uplink channel *** the channel estimation results are used for downlink transmission precoding,which will further affects the downlink *** paper analyses the impact of different pilot allocation(PA) schemes on downlink *** theoretical analysis,the system downlink signal to interference plus noise ratio(SINR) and spectral efficiency expressions of different pilot allocation schemes are obtained *** simulation results show that the pilot allocation schemes with cell grouping is better than the schemes without cell *** SINR increases as the number of cell grouping increases,and the spectrum efficiency increases first and then decreases as the number of cell grouping increases.

关键词： TDD The Downlink Performance of Massive MIMO Systems under Different Uplink Pilot Allocation Schemes

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A BVP signal Detection Method of Anti-Motion Interference

A BVP Signal Detection Method of Anti-Motion Interference

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International Congress on Image and signal processing, BioMedical Engineering and Informatics

作者： Qing Wan Xiaopei Wu Chao Zhang Anhui University Intelligent Computing and Signal Processing Key Lab Hefei China

The noncontact detection methods of blood volume pulse (BVP) based on facial videos have become a hot spot in recent years. However, these kinds of methods are highly sensitive to face movement. To address this problem, a novel BVP detection method based on kanade-lucas-tomasi (KLT) and independent component analysis (ICA) was proposed, in which, KLT method was employed for tracking and locating the region of interest (ROI) in facial images, and ICA method was used to improve the signal to noise ratio (SNR) of BVP signal. Based on 120 recorded facial videos, we carried out the comparative study of the proposed method and other commonly-used methods, the experimental results show that our method has obvious advantages in eliminating motion interference. In the implementation of the blind source separation method, we also conducted four separation methods. The results show that the second order blind identification (SOBI) algorithm is the best one to separate the BVP signal.

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Dependency forest for statistical machine translation

Dependency forest for statistical machine translation

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Tu, Zhaopeng Liu, Yang Hwang, Young-Sook Liu, Qun Lin, Shouxun Key Lab. of Intelligent Info. Processing Institute of Computing Technology Chinese Academy of Sciences China HILab Convergence Technology Center C and I Business SKTelecom China

We propose a structure called dependency forest for statistical machine translation. A dependency forest compactly represents multiple dependency trees. We develop new algorithms for extracting string-to dependency rules and training dependency language models. Our forest-based string-to-dependency system obtains significant improvements ranging from 1.36 to 1.46 BLEU points over the tree-based baseline on the NIST 2004/2005/2006 Chinese-English test sets.

关键词： Computer aided language translation

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GPU based fast algorithm for tanner graph based image interpolation

GPU based fast algorithm for tanner graph based image interp...

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3rd IEEE International Workshop on Multimedia signal processing, MMSP 2011

作者： Lei, Wei Xiong, Ruiqin Ma, Siwei Liang, Luhong Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100190 China Institute of Digital Media Peking University Beijing 100871 China

ISBN: (纸本)9781457714337

In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy effect compared with other adaptive methods such as NEDI, SAI. Tanner graph based image interpolation algorithm has better effect in dealing with edge and texture, but with high computation complexity. Thanks to the high performance parallel processing capability of today's GPU, use of complex algorithms for real time application is becoming possible. In this paper, we present a fast algorithm for tanner graph based image interpolation and it's implementation on GPU. In our algorithm, the image model training process of tanner graph based image interpolation is greatly simplified. Experimental results show that the GPU implementation can be more than 47 times as fast as the CPU implementation. © 2011 IEEE.

关键词： Graphics processing unit

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Focused crawling with heterogeneous semantic information

Focused crawling with heterogeneous semantic information

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2008 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2008

作者： Huang, Rui Lin, Fen Shi, Zhongzhi Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China Graduate University Chinese Academy of Sciences 100049 Beijing China

ISBN: (纸本)9780769534961

Focused crawlers selectively retrieve Web documents that are relevant to a predefined set of topics. To intelligently make predictions and decisions about relevant URLs and web pages, different topic models have been introduced to represent topic-specific knowledge. Yet it is difficult to support semantic interoperability among different models. Moreover, some manually specified additional semantic information, such as semantic markups and social annotations, could not be effectively used to improve crawling. This paper proposes to boost focused crawling with four kinds of semantic models and semantic information, including thesauruses, categories, ontologies, and folksonomies. A statistical semantic association model is proposed to integrate different semantic models, represent heterogeneous semantic information, and support semantic relevance computation. A focused crawling framework is developed which adopts both keyword based contents and different kinds of additional information for relevance prediction and ranking. Experiments show that the proposed model and framework effectively integrates heterogeneous semantic information for focused crawling. © 2008 IEEE.

关键词： Websites

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Fusion of Polarization Image Using Bidimensional Empirical Mode Decomposition

Fusion of Polarization Image Using Bidimensional Empirical M...

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International Conference on Computer Science and Mechanical Automation

作者： Dexiang Zhang Zihong Chen Jiaxing Li Jingjing Zhang Key Lab. of Intelligent Computing and Signal Processing Anhui University The School of Electrical Engineering and Automation Anhui University

ISBN: (纸本)9781467391672

Empirical mode decomposition (EMD) provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Bidimensional empirical mode decomposition (BEMD) techniques decompose an image into several bidimensional intrinsic mode functions (BIMFs) and a bidimensional residue (BR). Firstly, several polarization images can be decomposed into several BIMFs with multi-scales using BEMD. For the BIMF coefficients, the teager energy-based method is used. For the each BIMF coefficients, the area-based teager energy larger value of information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused image. Experimental results show that the proposed algorithm gives more satisfactory results than the traditional image fusion algorithms in preserving the edges and texture information.

关键词： Bidimensional empirical mode decomposition Image decomposition Polarization image Image fusion

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ObjectSense: A scalab.e multi-objects recognition system based on partial-duplicate image retrieval 13

ObjectSense: A scalable multi-objects recognition system bas...

引用

3rd ACM International Conference on Multimedia Retrieval, ICMR 2013

作者： Wang, Shuang Xue, Yunfeng Chu, Lingyang Jiang, Yuhao Jiang, Shuqiang Key Lab. of Intelligent Information Processing Institute of Computing Tech. CAS Beijing China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781450320337

In this demo, we present ObjectSense, a scalab.e object recognition system that recognizes multiple objects present in a static image or in the camera frames. Instead of applying learning based recognition framework, this system identifies objects through Partial-Duplicate Image Retrieval (PDIR) based method. First, objects are identified by measuring the similarity between an incoming image and reference image corpus that are lab.led with the objects. To compute image similarities, we explore the Consistency Graph Model (CGM), which robustly rejects spatially inconsistent feature matches with the advantage of orientations and positions of local features. Then a kNN voting method is used to decide the object category based on the quantized image similarities. ObjectSense is scalab.e with promisingly high recall and accuracy, which fits well into recognition-guided shopping and human computer interaction. We built ObjectSense on two platforms, PC and Android. © 2013 Authors.

关键词： Object recognition

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Using global statistics to rank retrieval systems without relevance judgments

Using global statistics to rank retrieval systems without re...

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作者： Shi, Zhiwei Wang, Bin Li, Peng Shi, Zhongzhi Information Retrieval Group Center for Advanced Computing Research Institute of Computing Technology Beijing 100190 China Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100190 China

ISBN: (纸本)3642163262

How to reduce the amount of relevance judgments is an important issue in retrieval evaluation. In this paper, we propose a novel method using global statistics to rank retrieval systems without relevance judgments. In our method, a series of global statistics of a system, which indicate the percentage of its documents found by k out of all the N systems (k = 1, 2, ..., N), are selected, then a linear combination of the series of global statistics is utilized to fit the mean average precision (MAP) of the retrieval system. Optimal coefficients are obtained by linear regression. No human relevance judgments are required in the entire process. Compared with existing evaluation methods without relevance judgments, our method has two advantages. Firstly, it outperforms all early attempts. Secondly, it is adjustable for different effectiveness measurements, e.g. MAP, precision at n, and so forth. © 2010 IFIP.

关键词： Information retrieval

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Are school-of-thought words characterizable?

Are school-of-thought words characterizable?

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51st Annual Meeting of the Association for Computational Linguistics, ACL 2013

作者： Jiang, Xiaorui Sun, Xiaoping Zhuge, Hai Key Lab. of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Nanjing University of Posts and Telecommunications Nanjing China Aston University Birmingham United Kingdom

ISBN: (纸本)9781937284510

School of thought analysis is an important yet not-well-elab.rated scientific knowledge discovery task. This paper makes the first attempt at this problem. We focus on one aspect of the problem: do characteristic school-of-thought words exist and whether they are characterizable? To answer these questions, we propose a probabilistic generative School-Of-Thought (SOT) model to simulate the scientific authoring process based on several assumptions. SOT defines a school of thought as a distribution of topics and assumes that authors determine the school of thought for each sentence before choosing words to deliver scientific ideas. SOT distinguishes between two types of school-of-thought words for either the general background of a school of thought or the original ideas each paper contributes to its school of thought. Narrative and quantitative experiments show positive and promising results to the questions raised above © 2013 Association for Computational Linguistics. © 2013 Association for Computational Linguistics.

关键词： Data mining

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Joint tokenization and translation

Joint tokenization and translation

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Xiao, Xinyan Liu, Yang Hwang, Young-Sook Liu, Qun Lin, Shouxun Key Lab. of Intelligent Info. Processing Institute of Computing Technology Chinese Academy of Sciences China HILab Convergence Technology Center C and I Business SKTelecom China

As tokenization is usually ambiguous for many natural languages such as Chinese and Korean, tokenization errors might potentially introduce translation mistakes for translation systems that rely on 1-best tokenizations. While using lattices to offer more alternatives to translation systems have elegantly alleviated this problem, we take a further step to tokenize and translate jointly. Taking a sequence of atomic units that can be combined to form words in different ways as input, our joint decoder produces a tokenization on the source side and a translation on the target side simultaneously. By integrating tokenization and translation features in a discriminative framework, our joint decoder outperforms the baseline translation systems using 1-best tokenizations and lattices significantly on both Chinese- English and Korean-Chinese tasks. Interestingly, as a tokenizer, our joint decoder achieves significant improvements over monolingual Chinese tokenizers.

关键词： Decoding

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