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IEEE International Conference on Automation Science and Engineering

作者： Yubin LIN Mengzhen KANG Jing HUA National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781467304290

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysts method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs.

关键词： Sensitivity analysis plant models organ growth MACHINE SHOP PRACTICE

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Misclassification and margin based SVM active learning algorithm for audio event detection

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International Journal of Advancements in Computing Technology 2011年第9期3卷 90-97页

作者： Leng, Yan Liu, Gang Qi, Guanghui Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China College of Physics and Electronics Shandong Normal University Jinan 250014 China Department of Construction Machinery Shandong Jiaotong University Jinan 250023 China

Audio event detection has become a hot research due to its wide applications in many fields, such as multimedia retrieval etc., the detection needs large amounts of labeled samples to train the audio event models, but in real life, the labeled samples are expensive to obtain, the shortage of such labeled samples is a big obstacle. Active learning is an efficient way to deal with the problem of insufficient labeled samples. The most popular support vector machines active learning is the margin based sampling (MBS), which is to query the sample closest to the current hyperplane, but when the current hyperplane is far away from the true hyperplane, the sample closest to the current hyperplane is not so informative, querying such samples would have a much slower adjustment of the hyperplane. In order to accelerate the adjustment, this paper proposes the misclassification and margin based sampling (MMBS) active learning algorithm. In order to query more informative samples, MMBS selects samples based on misclassified samples' KL divergence in the first few iterations, after that, considering the lower misclassification confidence and the outlier problem, it switches to MBS. Experiments show that compared to MBS and representative sampling (RepS), MMBS can get the highest detection performance under the same human annotation workload.

关键词： Support vector machines

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Extraction of affine invariant features for shape recognition based on ant colony optimization

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Journal of systems Engineering and Electronics 2011年第6期22卷 1003-1009页

作者： Yuxing Mao Ching Y. Suen Wei He State Key Laboratory of Power Transmission Equipment ＆ System Security and New Technology Chongqing University Chongqing 400044 E R. China Centre for Pattern Recognition and Machine Intelligence Concordia University Montreal QC H3G 1M8 Canada

A new approach to extraction of affine invariant features of contour image and matching strategy is proposed for shape ***,the centroid distance and azimuth angle of each boundary point are ***,with a prior-defined angle interval,all the points in the neighbor region of the sample point are considered to calculate the average distance for eliminating *** that,the centroid distance ratios（CDRs） of any two opposite contour points to the barycenter are achieved as the representation of the shape,which will be invariant to affine *** the angles of contour points will change non-linearly among affine related images,the CDRs should be resampled and combined sequentially to build one-by-one matching pairs of the corresponding *** core issue is how to determine the angle positions for sampling,which can be regarded as an optimization problem of path *** ant colony optimization（ACO）-based path planning model with some constraints is presented to address this ***,the Euclidean distance is adopted to evaluate the similarity of shape features in different *** experimental results demonstrate the efficiency of the proposed method in shape recognition with translation,scaling,rotation and distortion.

关键词： shape recognition affine transformation centroid distance ratio（CDR） ant colony optimization（ACO） path planning.

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A novel keypoint detection in wavelet pyramid space

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2011年第6期5卷 55-62页

作者： Gao, Yanyan Zhang, Honggang Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and telecommunications Beijing China

keypoint detection is important for object recognition, image retrieval, mosaicing etc., and has attracted ample research. In this paper, we propose a novel wavelet-based detector (NWBD) based on the previous researches on keypoint detection. NWBD is performed in wavelet pyramid space, it extracts the local extrema of the energy map computed by intra-scale coefficient product (ISCP) as the candidate keypoint, and then discards some points by Hessian matrix. In the experiments, the novel detector was compared with Harris detector and SIFT detector by the evaluation of repeatability, and it achieved better performance for some scenes in the database provided by Mikolajcyzk and Schmid, such as wall, trees, and graffiti.

关键词： Object recognition

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Multi-feature content-based product image retrieval based on region of main object

Multi-feature content-based product image retrieval based on...

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8th International Conference on Information, Communications and Signal Processing, ICICS 2011

作者： Chai, Lunshao Zhang, Honggang Qin, Zhen Yu, Jie Qi, Yonggang Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Riverside Lab for Artificial Intelligence Research University of California Riverside Riverside CA United States

ISBN: (纸本)9781457700309

Content-based image retrieval (CBIR) has got an intense interest and seen considerable progress over the last decade. But most of the time it is only applied in laboratory. One important reason for this is the diversity of images. Different practical situations call for different taxonomy definitions of images, and lead to very different solutions. At present, and even in the foreseeable future, a general purpose CBIR system is not really possible. However, image search engines oriented at specific domains are feasible in technology and also have the actual demand. With the rapid development of electronic commerce, searching specific product by image has become one of the most attractive related research topics. In this paper, we propose a region-based method fit for the content-based retrieval of product images. The method focuses on two key issues: fast extraction of the main region, in which the product locates, as well as efficient shape and color features extraction. To show the validity of the proposed region-based method, compared experiments are carried out and illustrated on the PI 100 dataset. © 2011 IEEE.

关键词： Content based retrieval

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Tweets Reading Probability Analysis Based on Competing-Window Model

Tweets Reading Probability Analysis Based on Competing-Windo...

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International Conference on Intelligence Science and Information Engineering (ISIE)

作者： Jianjun Xie Chuang Zhang Ming Wu Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

In microgblogs, a user usually follows or is followed by many other users. The content updating and reading is a complex process involving intensive interactions among publishers and readers. It also forms the basis of information diffusion in social networks. In the situation of massive followers, tweets reading would heavily depend on user behaviors and interactions. The tweets reading probability (TRP) would be a vital parameter measuring the effectiveness and influence of tweets. Our work proposed a fundamental model, namely competing-window, to simulate the process of multi-node interactions and analyzed TRP in social network. Based on Sina Microblog, we built a standard data set and run massive experiments on empirical data to extract user behavior patterns. By adopting simulating approaches, TRP in a none-preference social network was obtained. The results indicate that typical TRP is about 8% and different user behaviors affect TRP differently.

关键词： Data mining Publishing Conferences Twitter Data models Analytical models

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Structural fingerprint based hierarchical filtering in song identification

Structural fingerprint based hierarchical filtering in song ...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Qiang Wang Gang Liu Zhiyuan Guo Jun Guo Xiaoyu Chen Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781612843483

Automatic song identification has long been a research focus. In this paper, a novel structural fingerprint based hierarchical filtering method is proposed and it consists of two parts: one is the generation of fingerprint with both long structural information and low collision, and the other is an efficient searching algorithm based on a set of selective 2-level filters. Experiments conducted on a database of 10,000 songs show that our approach is fast enough and can achieve the accuracy of 99.7% on 5 second clips with the SNR at 0db comparable to the state-of-the-art.

关键词： Fingerprint recognition Filtering Filtering algorithms Indexes Robustness Feature extraction

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MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

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2011 4th IEEE International Conference on Broadband Network & Multimedia Technology(第四届IEEE宽带网络与多媒体国际会议 4th IEEE IC-BNMT2011)

作者： Yanyan Gao Honggang Zhang Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China

Color and texture information are two important visual features of an image. In this paper, an efficient content-based image retrieval system is proposed based on color and texture feature. The color feature is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by color histogram. Texture feature is obtained by local binary pattern (LBP). When computing the similarity between query image and target images in the database, Gaussian normalization is exploited on the feature space and distant space. And then the linear combination of normalized distances for color and texture is performed to obtain the similarity as the index of image. The exhaustive search scheme is used for retrieval, and the evaluation criterion is precision and recall about the number of returned images. The results of experiments demonstrate the efficiency of the proposed system.

关键词： content-based image retrieval color feature texture feature multi-feature

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An Image Matching Evolutionary Algorithm Based on Hu Invariant Moments

An Image Matching Evolutionary Algorithm Based on Hu Invaria...

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2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

作者： Ruliang Zhang Lin Wang Key Laboratory of Pattern Recognition and Intelligent Control Guizhou University for NationalitiesGuiyang China

ISBN: (纸本)9781612848792

This paper presents an image matching evolutionary algorithm (called IMEA algorithm) based on Hu invariant moments. First, the population is initialized. A group of searched subgraphs is constructed. Second, the fitness function based on Hu invariant moments is designed. The seven Hu invariant moments of the template image and the searched subgraph are calculated. The Euclidean distance of Hu invariant moments is used to measure similarity between the template image and the searched subgraph. The template image and the searched subgraph are matched if these Euclidean distances are less than the set threshold. Finally, a new searched subgraph is constructed by means of a new evolutionary strategy. The new searched subgraph replaces the searched subgraph whose value of the fitness function is maximum. Experimental results demonstrate the great robustness and efficiency of the IMEA algorithm.

关键词： Hu invariant moments evolutionary algorithm euclidean distance image matching

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An effective document image deblurring algorithm

An effective document image deblurring algorithm

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作者： Chen, Xiaogang He, Xiangjian Yang, Jie Wu, Qiang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Centre for Innovation in IT Services and Applications University of Technology Sydney Australia Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781457703942

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method. © 2011 IEEE.

关键词： Image enhancement

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