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Adaptively feature matching via joint transformational-spatial clustering

Adaptively feature matching via joint transformational-spati...

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作者： Wang, Linbo Tan, Li Fang, Xianyong Guo, Yanwen Wan, Shaohua MOE Key Laboratory of Intelligent Computing and Signal Processing School of Computer Science and Technology Anhui University Hefei China National Key Lab for Novel Software Technology Nanjing University Nanjing China School of Information and Safety Engineering Zhongnan University of Economics and Law Wuhan China

The transformational and spatial proximities are important cues for identifying inliers from an appearance based match set because correct matches generally stay close in input images and share similar local transformations. However, most existing approaches only check one type of them or both types consecutively with manually set thresholds, and thus their matching accuracy and flexibility in handling large-scale images are limited. In this paper, we present an efficient clustering based approach to identify match inliers with both proximities simultaneously. It first projects the putative matches into a joint transformational-spatial space, where mismatches tend to scatter all around while correct matches gather together. A mode-seeking process based on joint kernel density estimation is then proposed to obtain significant clusters in the joint space, where each cluster contains matches mapping the same object across images with high accuracy. Moreover, kernel bandwidths for measuring match proximities are adaptively set during density estimation, which enhances its applicability for matching different images. Experiments on three standard datasets show that the proposed approach delivers superior performance on a variety of feature matching tasks, including multi-object matching, duplicate object matching and object retrieval. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Clustering Density estimation Feature matching Mode-seeking

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An Energy-Efficient TDMA MAC for Wireless Sensor Networks

An Energy-Efficient TDMA MAC for Wireless Sensor Networks

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IEEE Asia-Pacific Conference on Services computing (APSCC)

作者： Rong Gang Bai Yu Gui Qu Yang Guo Bao Hua Zhao Department of Electronic Engineering and Information Science University of Science and Technology Hefei Anhui China Department of Computer Science Anhui Province Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China

This paper proposes an energy-efficient and collision-free medium access control protocol TDMA-WSN for wireless sensor networks. The protocol is based on time division multiple access (TDMA) principle and reduces energy consumption by avoiding overhearing, collision and idle listening. Nodes in TDMA-WSN build schedules based on information about their neighborhood to determine when they can transmit to their neighbors and when they should listen to the channel or sleep. TDMA-WSN proposes a novel resolution with three-d-hop neighborhood information to avoid collision caused by the two-hop collision-free principle used in some protocols. TDMA-WSN can accelerate passing message by arranging schedule based on routing information from the upper-layer. The simulation results indicate that TDMA-WSN outperforms contention-based protocols (e.g., S-MAC) and scheduling-based protocols (e.g., NAMA) with significant energy savings.

关键词： Energy efficiency Time division multiple access Wireless sensor networks Access protocols Media Access Protocol Wireless application protocol Energy consumption Sleep Energy resolution Acceleration

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Concurrent subspaces analysis

Concurrent subspaces analysis

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2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

作者： Xu, Dong Yan, Shuicheng Zhang, Lei Zhang, Hong-Jiang Liu, Zhengkai Shum, Heung-Yeung MOE-Microsoft Key Laboratory of Multimedia Computing and Communication Department of EEIS University of Science and Technology of China Hefei Anhui China Department of Information Engineering Chinese University of Hong Kong Shatin Hong Kong Microsoft Research Asia Beijing China

ISBN: (纸本)0769523722

A representative subspace is significant for image analysis, while the corresponding techniques often suffer from the curse of dimensionality dilemma. In this paper, we propose a new algorithm, called Concurrent Subspaces Analysis (CSA), to derive representative subspaces by encoding image objects as 2 nd or even higher order tensors. In CSA, an original higher dimensional tensor is transformed into a lower dimensional one using multiple concurrent subspaces that characterize the most representative information of different dimensions, respectively. Moreover, an efficient procedure is provided to learn these subspaces in an iterative manner. As analyzed in this paper, each sub-step of CSA takes the column vectors of the matrices, which are acquired from the k-mode unfolding of the tensors, as the new objects to be analyzed, thus the curse of dimensionality dilemma can be effectively avoided. The extensive experiments on the 3rd order tensor data, simulated video sequences and Gabor filtered digital number image database show that CSA outper-forms Principal Component Analysis in terms of both reconstruction and classification capability. © 2005 IEEE.

关键词： Image analysis

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Graph embedding: A general framework for dimensionality reduction

Graph embedding: A general framework for dimensionality redu...

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2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

作者： Yan, Shuicheng Xu, Dong Zhang, Benyu Zhang, Hong-Jiang Department of Information Engineering Chinese University of Hong Kong Shatin Hong Kong MOE-Microsoft Key Laboratory of Multimedia Computing and Communication Department of EEIS University of Science and Technology of China Hefei Anhui China Microsoft Research Asia Beijing China

ISBN: (纸本)769523722

In the last decades, a large family of algorithms - supervised or unsupervised;stemming from statistic or geometry theory - have been proposed to provide different solutions to the problem of dimensionality reduction. In this paper, beyond the different motivations of these algorithms, we propose a general framework, graph embedding along with its linearization and kernelization, which in theory reveals the underlying objective shared by most previous algorithms. It presents a unified perspective to understand these algorithms; that is, each algorithm can be considered as the direct graph embedding or its linear/kernel extension of some specific graph characterizing certain statistic or geometry property of a data set. Furthermore, this framework is a general platform to develop new algorithm for dimensionality reduction. To this end, we propose a new supervised algorithm, Marginal Fisher Analysis (MFA), for dimensionality reduction by designing two graphs that characterize the intra-class compactness and inter-class separability, respectively. MFA measures the intra-class compactness with the distance between each data point and its neighboring points of the same class, and measures the inter-class separability with the class margins; thus it overcomes the limitations of traditional Linear Discriminant Analysis algorithm in terms of data distribution assumptions and available projection directions. The toy problem on artificial data and the real face recognition experiments both show the superiority of our proposed MFA in comparison to LDA. © 2005 IEEE.

关键词： Embedded systems

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Design and Implementation of Links Generation for Inter Domain Routing System 12

Design and Implementation of Links Generation for Inter Doma...

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12th International Conference on Information Science and Technology, ICIST 2022

作者： Wang, Yu Qiao, Zhi Yin, Junru Zhang, Mingliang College of Software Henan University of Engineering Zhengzhou China College of Information and Electrical Engineering China Agriculture University Beijing China College of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Network Research Department Zhengzhou China

ISBN: (数字)9781665485821

ISBN: (纸本)9781665485821

Due to the inherent flaws of BGP protocol, the security of inter domain routing system has been regularly threatened. Since it is difficult to achieve collaborative defense against existing resources and strategies of multiple autonomous systems, this paper designs and organizes them into autonomous system community. Within the community, a precomputing multi-link generation mechanism is proposed based on genetic algorithm. Before the inter domain routing system is attacked, the link set can be generated as complete as possible in advance. Once an attack occurs, the community will quickly select proper precomputing links to replace the failed ones, in order to ensure the stability of inter domain communication. The effectiveness of the mechanism has been proved in function and performance through simulation experiments. © 2022 IEEE.

关键词： Genetic algorithms

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Fast fourier transform based ip traffic classification system for SIPTO at H(e)NB

Fast fourier transform based ip traffic classification syste...

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2012 7th International ICST Conference on communications and Networking in China, CHINACOM 2012

作者： Han, Lin Huang, Liusheng Hu, Qian Han, Xue Shi, Jinglin School of Software and Engineering University of Science and Technology of China Suzhou China Wireless Communication Technology Research Center Institute of Computing Technology Chinese Academy of Sciences China Beijing Key Laboratory of Mobile Computing and Pervasive Device China Beijing Sylincom Technologies Co. Ltd. China

ISBN: (纸本)9781467326995

3GPP has recently introduced LIPA(Local IP Access) and SIPTO(Selected IP Traffic Offload) to offload traffic from the core network, which brings new challenge to on-line traffic classification, because of the large amount of data and the difference of mobile network from wired network, such as high bit error rates(BER) and temporary disconnections. Therefore, other proposed schemes which aim at ether LIPA at H(e)NB or SIPTO at macro network could not get high accuracy and high speed at the same time, and traffic classification methodologies in wired IP network are not applicable. This paper proposes a fast fourier transform(FFT) based IP traffic classification system for SIPTO at H(e)NB, which focuses on classifying each packet at H(e)NB by extracting the application layer payload pattern using FFT. Pattern extraction and classification using machine learning algorithms are simulated, and results show that our system outperforms existing methods by offering about 3%-6% improvement in classification accuracy with about 7% time. Simulation of SIPTO shows good reduction of press to the core network and low false rates. © 2012 IEEE.

关键词： Fast Fourier transforms

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Multi-Layer Visual Perception for No-Reference Image Quality Assessment 6

Multi-Layer Visual Perception for No-Reference Image Quality...

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6th IEEE International Conference on Electronic Information and communication Technology, ICEICT 2023

作者： Qi, Junwei Wang, Yingzhen Wang, Qingchun Li, Yingsong College of Computer Science and Technology Harbin Engineering University Harbin150001 China College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Shanghai Yanding Information Technology Co. Ltd. Shanghai201210 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui Hefei230601 China

ISBN: (纸本)9798350399059

In this work, we propose a no-reference image quality evaluation approach, aiming to solve the problem that the traditional convolutional neural network is insufficient to express the global information of the image. Therefore, in order to make the captured image features have the coherence of global context information, we combine a Transformer structure widely used in NLP (natural language processing) with the traditional CNN to realize the attention mechanism in the human visual perception characteristics. Firstly, the self-attention mechanism of Transformer is used to learn the global representation of the image from the multi-layer features extracted from different levels of CNN. Additionally, to forecast the ultimate image quality score, the global and local attributes are combined. Finally, the proposed algorithm is evaluated on three public datasets commonly used in CSIQ [1], TID2013 [2] and LIVE [3]. Compared with eight traditional no-reference image quality evaluation algorithms and five methods based on deep learning, the proposed algorithm achieves competitive results. © 2023 IEEE.

关键词： Convolutional neural networks

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Representative Template Set Generation Method for Pedestrian Detection

Representative Template Set Generation Method for Pedestrian...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Pei Wu Xian-Bin Cao Yan-Wu Xu Hong Qiao Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China Institute of Automation Chinese Academy and Sciences Beijing China

Template matching is an effective approach for pedestrian detection. In order to achieve real-time and accurate detection, how to obtain a suitable representative template set is still an open problem due to the large variety of pedestrian shape. This paper introduced a representative template generation method for a template matching based pedestrian detection system (PDS). Based on nonlinear manifold learning and clustering, the new approach can generate a suitable representative template subset from a large amount of original templates. First, an improved nonlinear dimensionality reduction method was proposed to map original templates to feature vectors (points) in the low-dimensional embedding space; second, representative points were generated in the embedding space by clustering; at the end, corresponding representative template set were synthesized by mapping inversely the newly generated points from the embedding space to the visual input *** experimental results showed that the template generation method speeds up detection procedure without considerable loss of performance.

关键词： Shape Laboratories communication system software Vehicle detection Fuzzy systems Automation Performance loss Vehicles Object detection Pattern matching

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DFTCP: A TCP-friendly delay-based high-speed TCP variant

DFTCP: A TCP-friendly delay-based high-speed TCP variant

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International Conference on Networking and Network Applications (NaNA)

作者： Xu Zhang Naijie Gu Junjie Su Kaixin Ren Anhui Province Key Laboratory of Computing and Communication Software Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei China

Due to the conservative additive increase and multiplicative decrease strategy, traditional TCP has a severe problem in utilizing bandwidth over high-speed long-distance networks. This paper proposes a delay-based congestion control algorithm, named DFTCP, for these networks. DFTCP calculates a reasonable equilibrium point for a network flow based on the estimation of the maximum size of available buffers along its network path, and adjusts the congestion window size according to the distance between the equilibrium point and the current network state. The experimental results demonstrate that, the new algorithm performs well in terms of bandwidth utilization, intra-protocol fairness and RTT fairness, and exhibits reasonable friendliness to standard TCP.

关键词： Delays Standards Packet loss Throughput Bandwidth Convergence

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The Learning-Bargaining Algorithm Used in Unlicensed Spectrum Pre-Allocation

The Learning-Bargaining Algorithm Used in Unlicensed Spectru...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Kun Han Jinlong Li Ping Zhu Xufa Wang Anhui Province Key Laboratory of Software in Computing and Communication Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China

In the wireless network of finite spectrum resource, some communication users probably do not allocate the spectrum so that their communication should be delayed. Thus it is necessary to arrange the communication time of the systems when we allocate the communication spectrum. We propose a games learning-bargaining algorithm to pre-allocate the communication resources in the frequency-time space. Through this distributed games learning, each user obtains its communication schedule, and the result of allocation is further improved by the bargaining process. The result of this algorithm makes the bandwidth utilization achieve a quite high level and arranges the global communication time as short as possible. Comparing with the centralized algorithm of NP-hard, this distributed algorithm has low time complexity. The experiments verify the convergence of the algorithm and present the superiorities of our results to other allocation algorithms.

关键词： Cognitive Radio Spectrum Allocation Game Theory Learning-Bargaining Time Complexity.

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