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RETRACTED: Dual-mode predictive flexible rotor control for active magnetic bearings with input constraints

Journal of Vibration and Control 2016年第20期23卷 NP2页

作者： Yue Wu Jie Zhao Hai-Tao Zhang Ming-Can Fan Xi Yu Guangdong HUST Industrial Technology Research Institute Guangdong Province Key Lab of Digital Manufacturing Equipment ChinaKey Laboratory of Image Processing and Intelligent Control School of Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control School of Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology China Department of Mathematics Huizhou University China School of Electrical and Information Engineering Xi'an Technology University China

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Adaptive tag selection for image annotation 15

Adaptive tag selection for image annotation

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15th Pacific-Rim Conference on Multimedia, PCM 2014

作者： He, Xixi Li, Xirong Yang, Gang Xu, Jieping Jin, Qin Key Lab of DEKE Renmin University of China 100872 China Multimedia Computing Lab Renmin University of China 100872 China Shanghai Key Laboratory of Intelligent Information Processing 200443 China

ISBN: (纸本)9783319131672

Not all tags are relevant to an image, and the number of relevant tags is image-dependent. Although many methods have been proposed for image auto-annotation, the question of how to determine the number of tags to be selected per image remains open. The main challenge is that for a large tag vocabulary, there is often a lack of ground truth data for acquiring optimal cutoff thresholds per tag. In contrast to previous works that pre-specify the number of tags to be selected, we propose in this paper adaptive tag selection. The key insight is to divide the vocabulary into two disjoint subsets, namely a seen set consisting of tags having ground truth available for optimizing their thresholds and a novel set consisting of tags without any ground truth. Such a division allows us to estimate how many tags shall be selected from the novel set according to the tags that have been selected from the seen set. The effectiveness of the proposed method is justified by our participation in the ImageCLEF 2014 image annotation task. On a set of 2,065 test images with ground truth available for 207 tags, the benchmark evaluation shows that compared to the popular top-k strategy which obtains an F-score of 0.122, adaptive tag selection achieves a higher Fscore of 0.223. Moreover, by treating the underlying image annotation system as a black box, the new method can be used as an easy plug-in to boost the performance of existing systems. © Springer International Publishing Switzerland 2014.

关键词： Image annotation

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A Novel Subpixel Curved Edge Localization Method

A Novel Subpixel Curved Edge Localization Method

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International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2015

作者： Zhengyang Du Wenqiang Zhang Jinxian Qin Hong Lu Zhong Chen Xidian Zheng Shanghai Engineering Research Center for Video Technology and System School of Computer ScienceFudan University Shanghai Key Lab of Intelligent Information Processing School of Computer ScienceFudan University Shanghai Electric Group CO. LTD.Central Academe

With the high-speed development of digital image processing technology,machine vision technology has been widely used in automatic detection of industrial products.A large amount of products can be treated by computer instead of human in a shorter *** the process of automatic detection,edge detection is one of the most commonly used *** with the increasing demand for detection precision,traditional pixel-level methods are difficult to meet the requirement,and more subpixel level methods are in the *** paper presents a new method to detect curved edge with high ***,the target area ratio of pixels near the edge is computed by using one-dimensional edge detection ***,parabola is used to approximately represent the curved *** we select appropriate parameters to obtain accurate *** method is able to detect curved edges in subpixel level,and shows its practical effectiveness in automatic measure of products with arc shape in large industrial scene.

关键词： Machine vision curved edge detection subpixel parabola approximation

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Association rules mining algorithm using sharing mechanism niche leaping ant colony based on apriori algorithm

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Journal of Computational and Theoretical Nanoscience 2015年第10期12卷 3223-3231页

作者： Wang, Yang Xu, Yakun Li, Gang Wang, Hongliang MicroNano System Research Center College of Information Engineering Taiyuan University of Technology Taiyuan Shanxi China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of Technology Taiyuan Shanxi China Ministry of Education North University of China Taiyuan China

Based on the alarm data in the information communication network under the context of big data, the paper discusses the classic association mining algorithms of Apriori and FP-Growth with living examples, elaborates the ant colony algorithm and the niche technology, combines the Apriori algorithm thought and the Travelling Salesman Problem (TSP) of the ant colony algorithm, and proposes association rules mining algorithm using Sharing mechanism Niche Leaping Ant Colony based on Apriori algorithm (SN-APLAC algorithm). The algorithm achieves the thought of "leaping ants" by accelerating support calculation through a sparse linked list and setting the route point of non frequent item sets as "stimulation point" and retains the local optimal solution to further improve the quality of association rules mining utilizing the technique of sharing mechanism niche. Copyright © 2015 American Scientific Publishers.

关键词： Association rules

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Hierarchical Extreme Learning Machine for Unsupervised Representation Learning

Hierarchical Extreme Learning Machine for Unsupervised Repre...

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International Joint Conference on Neural Networks

作者： Wentao Zhu Jun Miao Laiyun Qing Guang-Bin Huang Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 China School of Electrical & Electronic Engineering Nanyang Technological University Nanyang Avenue Singapore 639798

ISBN: (纸本)9781479919611

Learning representations from massive unlabeled data is a hot topic for high-level tasks in many applications. The recent great improvements on benchmark data sets, which are achieved by increasingly complex unsupervised learning methods and deep learning models with lots of parameters, usually require many tedious tricks and much expertise to tune. However, filters learned by these complex architectures are quite similar to standard hand-crafted features visually, and training the deep models costs quite long time to fine-tune their weights. In this paper, Extreme Learning Machine-Autoencoder (ELM-AE) is employed as the learning unit to learn local receptive fields at each layer, and the lower layer responses are transferred to the last layer (trans-layer) to form a more complete representation to retain more information. In addition, some beneficial methods in deep learning architectures such as local contrast normalization and whitening are added to the proposed hierarchical Extreme Learning Machine networks to further boost the performance. The obtained trans-layer representations are followed by block histograms with binary hashing to learn translation and rotation invariant representations, which are utilized to do high-level tasks such as recognition and detection. Compared to traditional deep learning methods, the proposed trans-layer representation method with ELM-AE based learning of local receptive filters has much faster learning speed and is validated in several typical experiments, such as digit recognition on MNIST and MNIST variations, object recognition on Caltech 101. State-of-the-art performances are achieved on both Caltech 101 15 samples per class task and 4 of 6 MNIST variations data sets, and highly impressive results are obtained on MNIST data set and other tasks.

关键词： Hierarchical Extreme Learning Machine Unsupervised Representation Learning deep learning models Learning machines Dataset representation method Recognition (Psychology) Receptive field Learning representations Religious Missions Hierarchical

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Signal processing for the 5G Revolution

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IEEE SIGNAL processing MAGAZINE 2014年第6期31卷 12-13页

作者： Heath, Robert W., Jr. Leus, Geert Quek, Tony Q. S. Talwar, Shilpa Zhou, Peiying Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China Department of Computer Systems University of São Paulo - USP São Carlos Brazil IRISA Research Institute University of South Brittany - IRISA/UBS Vannes France

The articles in this special section provide an overview of recent advances in signal processing for communication with an emphasis on signal processing techniques that will be relevant for 5G cellular systems. It covers a wide range of topics including modulation, beamforming, cross-layer optimization based on different performance metrics, location-aware communication, cloud computing, and cloud radio access networks. The articles provide a diverse perspective on the potential challenges in 5G cellular systems.

关键词： Special issues and sections 5G mobile communication Next generation networking Wireless communication Cellular networks Wireless cellular networks

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Fusion of polarization image based on curvelet transform

Fusion of polarization image based on curvelet transform

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2014 2nd International Conference on Mechatronics, Robotics and Automation, ICMRA 2014

作者： Zhang, De Xiang Wang, Hong Hai Xue, Feng The Department of Information and Communication Technology Anhui Sanlian University Hefei 230601 China Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)9783038350781

Curvelet transform is the combination of the multi-scale analysis and multi-directional analysis transforms, which is more suitable for objects with curves. Applications of the curvelet transform have increased rapidly in the field of image fusion. Firstly, using the curvelet transform, several polarization images can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions. For the low-frequency coefficients, the average fusion method is used. For the each directional high frequency sub-band coefficients, the larger value of region variance 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 curvelet coefficients. In the present work an algorithm for image fusion based on the curvelet transform was implemented, analyzed, and compared with a wavelet-based fusion algorithm. Experimental results show that the proposed algorithm works better in preserving the edges and texture information compared with the wavelet-based image fusion algorithms. © (2014) Trans Tech Publications, Switzerland.

关键词： Image fusion

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Artifact reduction of compressed video via three-dimensional adaptive estimation of transform coefficients

Artifact reduction of compressed video via three-dimensional...

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作者： Zhang, Xinfeng Xiong, Ruiqin Ma, Siwei Gao, Wen Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Institute of Digital Media Peking University Beijing100871 China

ISBN: (纸本)9781479957514

Block transform compressed videos usually suffer from annoying artifacts at low bit rates, caused by the coarse quantization of transform coefficients. The inter prediction utilized in video coding also induces block boundary artifacts when the neighboring blocks using different motion vectors from previous decoded frames. In this paper, a three-dimensional adaptive estimation method for video transform coefficients is proposed to reduce the artifact in compressed video. In the proposed method, transform coefficients of each block are estimated by adaptively fusing three prediction sources based on their reliabilities. One prediction source is the transform coefficients directly acquired from the decoded video, whose reliability is determined by the distribution of the quantization noise. The other prediction source is derived by a temporal autoregressive model of transform-blocks along motion trajectory among neighboring reference frames. Its reliability is estimated from prediction variance of local blocks. The last prediction source is derived from the nonlocal transform-blocks, whose reliability is estimated based on the distribution of the nonlocal coefficients and their similarity with the estimated block. Experimental results for compressed video sequences by HEVC show that, the proposed method can reduce the compression artifacts and improve both the objective and subjective quality. © 2014 IEEE.

关键词： Forecasting

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A representative local region detector based on color-contrast-MSER 14

A representative local region detector based on color-contra...

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2014 4th ACM International Conference on Multimedia Retrieval, ICMR 2014

作者： Cao, Yang Gao, Ke Tang, Sheng Zhang, Yongdong Key Lab of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)1595930361

In order to extract representative local invariant regions in textured natural images, we propose a Color-Contrast-MSER (CCM) detector with color-contrast pixel ranking, which can reduce the number of meaningless regions extracted from backgrounds. The main contributions are threefold: (1) In contrast with the original MSER[3] which adopts intensity pixel ranking, we develop a new pixel ranking mechanism based on color contrast analysis. (2) In this paper, the pixel ranking value of each pixel is defined as the color contrast between a kernel-sized window and the background. Therefore we propose an adaptive background scale selection mechanism that simulates the background color distribution as the benchmark for color contrast. (3) The experimental results demonstrate that compared with the original MSER detector[3], our Color-Contrast-MSER (CCM) detector can extract more representative local regions with competitive repeatability score at only 50% computational time and 10% memory cost. Copyright 2014 ACM.

关键词： Pixels

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Collecting valuable information from fast text streams 8

Collecting valuable information from fast text streams

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8th IFIP International Conference on intelligent information processing, IIP 2014

作者： Qi, Baoyuan Ma, Gang Shi, Zhongzhi Wang, Wei Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Beijing Lexo Technologies Co. Ltd Beijing100080 China

ISBN: (纸本)9783662449790

It has become a challenging work to collect valuable information from fast text streams. In this work, we propose a method which gains useful information effectively and efficiently. Firstly, we maintain an analyzer based on the Trie structure and the dynamic N-Gram tokenizer;secondly, unlike the traditional search engine principle, we consider the documents as a query by building the indexes for the whole query base. The experimental results show that it has the strong adaption ability, low latency and high quality support for the complex query combination compared with the conventional methods. © IFIP International Federation for information processing 2014.

关键词： Search engines

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