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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Quan Yuan Yanjun Hu Hui Zhi Mengmeng He Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

Two-way relaying can considerably improve spectral efficiency in relay-assisted bidirectional ***,most existing works focus on physical layer to exploit its resource *** benefits and flexible structures of two-way relaying on datalink layer are much less *** in this paper,the cross-layer optimization for amplify-and-forward(AF)two-way relaying system is studied and an optimal power allocation scheme is *** goal is to find the optimal power allocation factors to maximize the weighted sum effective capacity of two sources in the physical layer while guaranteeing the statistical delay quality-of-service(QoS)requirement for each source in the datalink *** statistical delay Qo S requirement is characterized by the QoS exponentq,which is the only requested information exchanged between the physical layer and the datalink layer in our cross-layer design based *** integrating the concept of effective capacity,the cross-layer optimization problem is equivalent to a weighted sum effective capacity maximization *** problem is formulated into a convex optimization problem,and an algorithm is presented to solve this *** results show that proposed optimal power allocation scheme can achieve better weighted sum effective capacity than equal power allocation scheme and direct transmission scheme,and the relay transmission combined with direct links can get the max weighted sum effective capacity.

关键词： two-way relaying quality-of-service(Qo S) cross-layer optimization power allocation effective capacity

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Cross-Layer Power Allocation Scheme for Wireless Full Duplex Relaying System

Cross-Layer Power Allocation Scheme for Wireless Full Duplex...

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2016 8th IEEE International Conference on Communication Software and Networks(ICCSN 2016)

作者： Mengmeng He Yanjun Hu Hui Zhi Quan Yuan Key Lab of Intelligent Computing and Signal Processing Ministry of Education School of Electronics and Information Engineering Anhui University

In this paper,we propose a cross-layer power allocation scheme over wireless relay networks for quality-of-service(Qo S)*** formulate our original throughput maximization problem into effective capacity maximization problem by applying information theory and the concept of the effective *** our scheme,we focus on full duplex mode and amplify-and-forward(AF)*** particular,our proposed scheme derives closed-form expressions and analyzes the impacts of the SNR of the interference channel on the performance of full duplex relaying *** comparison purpose,we also give the analysis of half duplex relaying *** results show that our proposed power allocation scheme can support diverse Qo S guarantees and achieve better effective capacity than equal power allocation scheme and direct transmission *** analysis also indicate that the perfect full duplex mode can achieve twice optimal effective capacity of the half duplex mode.

关键词： power allocation scheme effective capacity full duplex quality-of-service(Qo S) amplify-and-forward(AF)

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GLAD: Global-local-alignment descriptor for pedestrian retrieval

arXiv

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arXiv 2017年

作者： Wei, Longhui Zhang, Shiliang Yao, Hantao Gao, Wen Tian, Qi School of Electronic Engineering and Computer Science Peking University Beijing100871 China Key Lab of Intelligent Information Processing of CAS Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Department of Computer Science University of Texas at San Antonio San AntonioTX78249-1604 United States

The huge variance of human pose and the misalignment of detected human images significantly increase the difficulty of person Re-Identification (Re-ID). Moreover, efficient Re-ID systems are required to cope with the massive visual data being produced by video surveillance systems. Targeting to solve these problems, this work proposes a Global-Local-Alignment Descriptor (GLAD) and an efficient indexing and retrieval framework, respectively. GLAD explicitly leverages the local and global cues in human body to generate a discriminative and robust representation. It consists of part extraction and descriptor learning modules, where several part regions are first detected and then deep neural networks are designed for representation learning on both the local and global regions. A hierarchical indexing and retrieval framework is designed to eliminate the huge redundancy in the gallery set, and accelerate the online Re-ID procedure. Extensive experimental results show GLAD achieves competitive accuracy compared to the state-of-the-art methods. Our retrieval framework significantly accelerates the online Re-ID procedure without loss of accuracy. Therefore, this work has potential to work better on person Re-ID tasks in real scenarios. Copyright © 2017, The Authors. All rights reserved.

关键词： Deep neural networks

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Summarization of Related Work through Citations 12

Summarization of Related Work through Citations

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12th International Conference on Semantics, Knowledge and Grids, SKG 2016

作者： Chen, Jingqiang Zhuge, Hai Nanjing University of Posts and Telecommunications 210023 Nanjing China. Key Lab of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences 100190 Beijing China. Systems Analytics Research Institute Aston University Birmingham UK

ISBN: (纸本)9781509047956

Automatically generating the related work section for a writing paper is useful for researchers as it can save a lot of time and avoid missing related works. The related work section of scientific paper usually introduces other researchers' work published before and makes comparisons with the current author's work. This paper proposes an approach to automatically generating related work by comparing the main text of the writing paper with the citations to the references from other papers. Our approach firstly collects the papers that cite the reference papers of the writing paper and extracts the corresponding citation sentences to form a citation document. It then makes a summarization that makes a comparison between the citation document and the writing paper's abstract, introduction and conclusion. It extracts the representative keywords from the citation document and the writing paper, and constructs a graph of the keywords. The discriminated nodes in the graph are figured out, and then the minimum Steiner tree that covers the nodes is extracted. A summary is generated by extracting the sentences covering the Steiner tree. The experiments show that our approach outperforms three baselines MEAD, ReWoS and ARWG according to ROUGE evaluation results. © 2016 IEEE.

关键词： Trees (mathematics)

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Cross-layer power allocation scheme for wireless full duplex relaying system

Cross-layer power allocation scheme for wireless full duplex...

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International Conference on Communication Software and Networks, ICCSN

作者： Mengmeng He Yanjun Hu Hui Zhi Quan Yuan Ministry of Education Key Lab of Intelligent Computing and Signal Processing China School of Electronics and Information Engineering Anhui University Hefei China

In this paper, we propose a cross-layer power allocation scheme over wireless relay networks for quality-of-service(QoS) guarantees. We formulate our original throughput maximization problem into effective capacity maximization problem by applying information theory and the concept of the effective capacity. In our scheme, we focus on full duplex mode and amplify-and-forward(AF) protocol. In particular, our proposed scheme derives closed-form expressions and analyzes the impacts of the SNR of the interference channel on the performance of full duplex relaying system. For comparison purpose, we also give the analysis of half duplex relaying system. Simulation results show that our proposed power allocation scheme can support diverse QoS guarantees and achieve better effective capacity than equal power allocation scheme and direct transmission scheme. Our analysis also indicate that the perfect full duplex mode can achieve twice optimal effective capacity of the half duplex mode.

关键词： Relays Resource management Quality of service Protocols Wireless communication Physical layer Signal to noise ratio

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Large-scale person re-identification as retrieval

Large-scale person re-identification as retrieval

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Hantao Yao Shiliang Zhang Dongming Zhang Yongdong Zhang Jintao Li Yu Wang Qi Tian University of Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China School of Electronic Engineering and Computer Science Peking University Beijing China National Computer Network Emergency Response Technical Team/Coordination Center of China Department of Computer Science University of Texas at San Antonio San Antonio USA

ISBN: (纸本)9781509060689

This paper targets to bring together the research efforts on two fields that are growing actively in the past few years: multicamera person Re-Identification (ReID) and large-scale image retrieval. We demonstrate that the essentials of image retrieval and person ReID are the same, i.e., measuring the similarity between images. However, person ReID requires more discriminative and robust features to identify the subtle differences of different persons and overcome the large variance among images of the same person. Specifically, we propose a coarse-to-fine (C2F) framework and a Convolutional Neural Network structure named as Conv-Net to tackle the large-scale person ReID as an image retrieval task. Given a query person image, the C2F firstly employ Conv-Net to extract a compact descriptor and perform the coarse-level search. A robust descriptor conveying more spatial cues is hence extracted to perform the fine-level search. Extensive experimental results show that the proposed method outperforms existing methods on two public datasets. Further, the evaluation on a large-scale Person-520K dataset demonstrates that our work is significantly more efficient than existing works, e.g., only needs 180ms to identify a query person from 520K images.

关键词： Training Feature extraction Cameras Robustness Image retrieval Linear programming

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A local-optimization refinement algorithm in single particle analysis for macromolecular complex with multiple rigid modules

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Protein & Cell 2016年第1期7卷 46-62页

作者： Hong Shan Zihao wang Fa Zhang Yong Xiong Chang-Cheng Yin Fei Sun Department of Biophysics College of Basic Medical Sciences Peking University Health Science Center Beijing 100191China National Laboratory of Biomacromolecules Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China Key Lab of Intelligent Information Processing and Advanced Computing Research Lab Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06511 USA Center for Biological Imaging Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China

Single particle analysis, which can be regarded as an average of signals from thousands or even millions of particle projections, is an efficient method to study the three-dimensional structures of biological macro- molecules. An intrinsic assumption in single particle analysis is that all the analyzed particles must have identical composition and conformation. Thus specimen heterogeneity in either composition or conformation has raised great challenges for high-resolution analysis. For particles with multiple conformations, inaccurate align- ments and orientation parameters will yield an averaged map with diminished resolution and smeared density. Besides extensive classification approaches, here based on the assumption that the macromolecular complex is made up of multiple rigid modules whose relative orien- tations and positions are in slight fluctuation around equilibriums, we propose a new method called as local optimization refinement to address this conformational heterogeneity for an improved resolution. The key idea is to optimize the orientation and shift parameters of each rigid module and then reconstruct their three-dimen- sional structures individually. Using simulated data of 80S/70S ribosomes with relative fluctuations between the large （60S/50S） and the small （40S/30S） subunits, we tested this algorithm and found that the resolutions of both subunits are significantly improved. Our method provides a proof-of-principle solution for high-resolutionsingle particle analysis of macromolecular complexes with dynamic conformations.

关键词： cryo-electron microscopy single particleanalysis conformational heterogeneity rigid module Iocaoptimization refinement

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Learning from multi metrics for stereoscopic 3D image quality assessment

Learning from multi metrics for stereoscopic 3D image qualit...

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International Conference on 3D Imaging (IC3D)

作者： Jiamei Zhan Yuzhen Niu Yize Huang College of Mathematics and Computer Science. Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Quality assessment of stereoscopic 3D images is much more complex than that of 2D images. Quality assessment metrics for 3D images have achieved good performance on symmetric distorted 3D images, while given poor performance on asymmetric distorted 3D images. To further improve the perception consistency for symmetric and asymmetric distorted 3D images, this paper presents a machine learning-based full-reference 3D image quality assessment method that learns from multi IQA metrics. Considering that changes in left view, right view and depth information all impact human perception, our method considers the quality of two views and depth information. Since symmetric and asymmetric distortions impact left and right views of a 3D image differently, we propose different features for symmetric and asymmetric distorted 3D images. The experimental results show that our method has better performance than both 2D-based 3D quality assessment metrics and the state of the art specially designed 3D quality assessment metrics.

关键词： Three-dimensional displays Measurement Distortion Indexes Two dimensional displays Image quality Stereo image processing

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An attribute reduction framework for inconsistent decision tables from view of the boundary region

An attribute reduction framework for inconsistent decision t...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jin Qian Yu-Hui Chang Ping Lv Jiangsu Key Laboratory of Big Data Analysis Technology/B-DAT Nanjing University of Information Science & Technology Nanjing China Key Laboratory of Cloud Computing and Intelligent Information Processing of Changzhou City Jiangsu University of Technology Changzhou China

ISBN: (纸本)9781509003914

Attribute reduction is one of the key issues for data preprocess in data mining. Many heuristic attribute reduction algorithms based on discernibility matrix have been proposed for inconsistent decision tables. However, these methods are usually computationally time-consuming. To address this issue, the derived consistent decision tables are defined for different definitions of relative reducts. The computations for different reducts of the original inconsistent decision tables are converted into the computations for their corresponding reducts of the derived consistent datasets. The relative discernibility object pair and the more optimal relative discernibility degree from view of the boundary region are designed to accelerate the attribute reduction process. An efficient attribute reduction framework using relative discernibility degree is proposed for large datasets. Experimental results show that our attribute reduction algorithms are effective and feasible for large inconsistent datasets.

关键词： Cybernetics Acceleration Time complexity Rough sets Heuristic algorithms Data mining Algorithm design and analysis

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Category aggregation among region proposals for object detection 17th

Category aggregation among region proposals for object detec...

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17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Li, Linghui Tang, Sheng Zhou, Jianshe Wang, Bin Tian, Qi Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing100190 China Beijing Advanced Innovation Center for Imaging Technology Capital Normal University Beijing100048 China Department of Computer Science University of Texas at San Antonio San AntonioTX78249-1604 United States

ISBN: (纸本)9783319488950

Recently, an overwhelming majority of object detection methods have focused on how to reduce the number of region proposals while keeping high object recall without consideration of category information. It may lead to a lot of false positives due to the interferences between categories especially when the number of categories is very large. To eliminate such interferences, we propose a novel category aggregation approach based upon our observation that more frequently detected categories around an object have the higher probabilities to be present in an image. After further exploiting the co-occurrence relationship between categories, we can determine the most possible categories for an image in advance. Thus, many false positives can be greatly filtered out before subsequent classification process. Our extensive experiments on the well-known ILSVRC 2015 detection dataset show that our approach can achieve 49.0% of mAP in the validation dataset and 45.36% of mAP in the test dataset ranked 5th in the ILSVRC 2015 detection task. © Springer International Publishing AG 2016.

关键词： Object detection

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