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8th International Conference on intelligent Text Processing and Computational Linguistics

作者： Xu, Lin Cao, Xiaoguang Zhang, Bufeng Li, Mu Lab. of Pattern Recognition and Intelligent System Image Processing Center BeiHang University China Al Lab. Computer Science and Technology Tianjing University China Microsoft Research Asia China

ISBN: (纸本)9783540709381

In statistical machine translation (SMT) research, phrase-based methods have been receiving more interest in recent years. In this paper, we first give a brief survey of phrase-based SMT framework, and then make detailed comparisons of two typical implementations: alignment template approach and standard phrase-based approach. At last, we propose an improved model to integrate alignment template into standard phrase-based SMT as a new feature in a log-linear model. Experimental results show that our method outperforms the baseline method.

关键词： Natural language processing systems

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AN EFFICIENT DUPLICATE IMAGE DETECTION METHOD BASED ON AFFINE-SIFT FEATURE

AN EFFICIENT DUPLICATE IMAGE DETECTION METHOD BASED ON AFFIN...

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2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

作者： Yudong Cao Honggang Zhang Yanyan Gao Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica

In this paper, we present a novel scheme to tackle the task of near-duplicate image detection. Given two input images, the algorithm based on the refined similarity measure can judge rightly whether two input image are duplicate images or not. The two images are represented with local feature (i.e, Affine-SIFT) in bag of features model. The Affine-SIFT can undergo larger affine distortions than Hessian-Affine and MSER (Maximally Stable Extremal Region). The refined similarity measure exploits the spatial information between two images. The algorithm is demonstrated on some image pairs with scale change, viewpoint change, blur, noise and spatial deformation. The experimental results show that proposed algorithm is more effective than other state-of-the-art duplicate image detection algorithm.

关键词： duplicate detection image matching Affine-SIFT

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NOVEL ACTIVE LEARNING SAMPLE EVALUATION METHOD BASED ON MULTI-LEVEL CONFUSION NETWORKS

NOVEL ACTIVE LEARNING SAMPLE EVALUATION METHOD BASED ON MULT...

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2010 2nd IEEE International Conference on Network Infrasturcture & Digital Content(2010年第二届IEEE网络基础设施与数字内容国际会议 IC-NIDC 2010)

作者： Wei Chen Jun Guo Gang Liu Pattern Recognition and Intelligent System LaboratoryBeijing University of Posts and Telecommunicati Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunicat

Active Learning (AL) is designed to aid the laborintensive process of training acoustic model for speech recognition. In AL, only the most informative training samples are selected for manual annotation. Thus, how to evaluate the unlabeled samples is worth researching. In this paper, we propose a unified framework to generate confusion networks of multiple levels including character, syllable and phone, and present a novel active learning sample evaluation method for Chinese acoustic modeling, posterior probabilities obtained from multi-level confusion networks are respectively adopted to evaluate the unlabeled samples. Our experiments show that compared with the widely used sample evaluation method using word posterior probability obtained from word confusion network, our proposed method can achieve satisfying performances.

关键词： Active learning confusion network acoustic model speech recognition

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Research on Low Altitude Aerial Image Stitching

Research on Low Altitude Aerial Image Stitching

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第37届中国控制会议

作者： Jiakun Lu Yongqiang Bai Beijing Institute of Technology Pattern Recognition and Intelligent System

In this paper, we study the problem of low altitude aerial image stitching. Though the traditional approach is well studied, batch-process image stitching is more difficult. In this work, we present a simple and effective approach to handle problems in low altitude aerial image stitching by considering GPS information of images and seam cutting algorithm. Our method develops an efficient approach to generate the flight path of UAV. We then select alternative images and calculate the overlapping region according to the distance between adjacent images. Features are efficiently detected not only in longitude overlap, but also in lateral, which largely improves stitching accuracy and decreases accumulative errors. In order to handle parallax caused by low altitude flight, we use seam finding method to avoid ghost. Experimental results show that our approach can effectively stitch a large number of images and successfully handle small parallax with low cost.

关键词： Aerial Image GPS Information Seam Cutting Image Registration Image Mosaic

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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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Mem Brain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

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Nano-Micro Letters 2018年第1期10卷 12-19页

作者： Xi Yin Jing Yang Feng Xiao Yang Yang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Computer Science Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem Brain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of a-helical membrane proteins. Mem Brain achieves aprediction accuracy of 97.9% of ATMH, 87.1% of AP,3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. Mem BrainContact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction,respectively. And Mem Brain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of13.593. These prediction results provide valuable hints for revealing the structure and function of membrane *** Brain web server is free for academic use and available at ***/bioinf/Mem Brain/.

关键词： Transmembrane a-helices Structure prediction Machine learning Contact map prediction Relative accessible surface area

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N-LBP BASED VEHICLE MONITORING system

N-LBP BASED VEHICLE MONITORING SYSTEM

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2009 IEEE International Conference on Network Infrastructure and Digital Content(2009年IEEE网络基础设施与数字内容国际会议 IEEE IC-NIDC2009)

作者： Kunyan Lan Jun Guo Wenting Lu Honggang Zhang Laboratory of Pattern Recognition and Intelligent System Beijing University of Posts and Telecommun Laboratory of Pattern Recognition and Intelligent System Beijing University of Posts and Telecommuni

ISBN: (纸本)9781424448999

In recent years, feature based object detection has attracted increasing attention in computer vision research community. However, to our best knowledge, no previous work has focused on utilizing local binary pattern (LBP) for vehicle detection in intelligent Transportation system（ITS） domain. In this paper, we develop a novel traffic monitoring system based on N-LBP algorithm, which is the new LBP texture descriptor proposed. The approach includes three steps: firstly the general critical ingredients (GCI for short) are selected from LBP features through training to indicate vehicles. Then GCI are extracted from region of interest (ROI) in the new image for object detection and identification. Linear Kalman filter is employed for feature based tracking finally. Experimental results demonstrate the superiority of N-LBP feature over basic LBP feature, and performance of the new system is more stable and reliable.

关键词： ITS vehicle detection vehicle tracking N-LBP Kalman filter

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A Distributed Vertical Crawler Using Crawling-Period Based Strategy

A Distributed Vertical Crawler Using Crawling-Period Based S...

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The 2010 2nd International Conference on Future Computer and Communication(第二届未来计算机与通信国际会议 ICFCC 2010)

作者： Bing Zhou Chuang Zhang Bo Xiao Zhiqing Lin Pattern Recognition and Intelligent System Beijing University of Posts and Telecommunications BUPT B Pattern Recognition and Intelligent System Beijing University of Posts and Telecommunications BUPT

ISBN: (纸本)9781424458219;9781424458240

Due to the explosive growth of the web pages, centralized crawlers are no longer sufficient to run on the web efficiently. There are many distributed crawlers in wide use;however, none of them is suitable for template-customized vertical crawling. In this paper, we present a distributed templatecustomized vertical crawler which is specially used for crawling Internet forums. The Client-Server architecture of the system and the function of every module are described in detail which can be extended to other fields easily. A crawling-period based distribution strategy is also proposed, with which the crawler manager can coordinate the quantity of crawling tasks and the resources of each crawler very well, and the crawler can process websites with different updating frequency flexibly. We also define a communication protocol between crawlers and crawler manager and describe how to solve the duplicated crawling problem in the distributed system. The performance of centralized vertical crawler and distributed vertical crawler are compared in the experiment. Experimental results demonstrate that the parallel operation of all the crawlers in the distributed system can greatly enhance the crawling efficiency.

关键词： distributed system vertical crawler crawler manager forum crawler Crawling-Period

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A NEW COMBINATION FEATURE OF S-LBP AND MAIN COLOR DESCRIPTOR FOR VIDEO FRAME RETRIEVAL

A NEW COMBINATION FEATURE OF S-LBP AND MAIN COLOR DESCRIPTOR...

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2010 2nd IEEE International Conference on Network Infrasturcture & Digital Content(2010年第二届IEEE网络基础设施与数字内容国际会议 IC-NIDC 2010)

作者： Lixia Liu Xinxin Wan Honggang Zhang Aiping Feng Jun Guo Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications B Pattern Recognition and Intelligent System Lab Beijing University of Posts and Telecommunications

In this paper, we draw Local Binary pattern (LBP) and main color descriptor into content-based video indexing and retrieval. LBP is a powerful texture descriptor for its tolerance against illumination changes and its computational simplicity. Main color descriptor is used for representing main color distribution of the image. We propose a simplified LBP (S-LBP) operator as the texture descriptor. In most cases, texture distributions that ignore the actual positions or spatial arrangement in the image are not sufficient for representing an image. Therefore, we use zigzag based Run-length coding principle to produce S-LBP patterns histogram. Then we apply the combination of S-LBP feature and main color descriptor to represent an image in video retrieval. The experiment that to retrieval which video a given frame comes from demonstrates the combination method is efficient and effective.

关键词： S-LBP Main color Key frames Image and Video retrieval

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An efficient duplicate image detection method based on Affine-SIFT feature

An efficient duplicate image detection method based on Affin...

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2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology, IC-BNMT2010

作者： Cao, Yudong Zhang, Honggang Gao, Yanyan Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China College of Electrical and Information Engineering Liaoning University of Technology Jinzhou China

ISBN: (纸本)9781424467709

关键词： Affine-SIFT Duplicate detection Image matching

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