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5th IEEE International Conference on Systems Biology, ISB 2011

作者： Wang, Mingjun Shen, Hong-Bin Akutsu, Tatsuya Song, Jiangning State Engineering Laboratory for Industrial Enzymes Tianjin Institute of Industrial Biotechnology Chinese Academy of Sciences Tianjin 300308 China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200240 China Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto 611-0011 Japan Department of Biochemistry and Molecular Biology Faculty of Medicine Monash University Melbourne VIC 3800 Australia

ISBN: (纸本)9781457716669

Single amino acid polymorphisms (SAPs) are the most abundant form of known genetic variations associated with human diseases. It is of great interest to study the sequence-structure-function relationship underlying SAPs. In this work, we collected the human variant data from three databases and divided them into three categories, i.e. cancer somatic mutations (CSM), Mendelian disease-related variant (SVD) and neutral polymorphisms (SVP). We built support vector machine (SVM) classifiers to predict these three classes of SAPs, using the optimal features selected by a random forest algorithm. Consequently, 280 sequence-derived and structural features were initially extracted from the curated datasets from which 18 optimal candidate features were further selected by random forest. Furthermore, we performed a stepwise feature selection to select characteristic sequence and structural features that are important for predicting each SAPs class. As a result, our predictors achieved a prediction accuracy (ACC) of 84.97, 96.93, 86.98 and 88.24%, for the three classes, CSM, SVD and SVP, respectively. Performance comparison with other previously developed tools such as SIFT, SNAP and Polyphen2 indicates that our method provides a favorable performance with higher Sensitivity scores and Matthew's correlation coefficients (MCC). These results indicate that the prediction performance of SAPs classifiers can be effectively improved by feature selection. Moreover, division of SAPs into three respective categories and construction of accurate SVM-based classifiers for each class provides a practically useful way for investigating the difference between Mendelian disease-related variants and cancer somatic mutations. © 2011 IEEE.

关键词： Amino acids

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DSA image registration based on multiscale Gabor filters and mutual information

DSA image registration based on multiscale Gabor filters and...

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International Conference on Information and Automation (ICIA)

作者： Zhiguo Cao Xiaoxiao Liu Bo Peng Yiu-Sang Moon Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Chinese University of Hong Kong New Territories Hong Kong China

In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in X-ray image sequences. Different with traditional DSA image registration processes, in our proposed image registration method, the control points are selected from the vessel centerlines using multiscale Gabor filters, and mutual information (MI) is then taken as the similarity criterion to find the correspondences. Experimental results demonstrate our algorithm efficiently yields satisfying registration result for DSA images.

关键词： image registration Gabor filters Mutual information Biomedical imaging Angiography Visualization Displacement control Blood vessels image sequences Pixel

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Efficient Face Segmentation Based on Face Attention Model and Seeded Region Merging

Efficient Face Segmentation Based on Face Attention Model an...

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9th International Conference on Signal processing(第九届国际信号处理学术会议)(ICSP'08)

作者： Zhi Liu Weiwei Li Xiang Zhang Jie Yang School of Communication and Information Engineering Shanghai UniversityChina Key Lab of Advanced Di School of Communication and Information Engineering Shanghai UniversityChina Institute of Image Processing and Pattern Recognition Shanghai Jiaotong UniversityChina

This paper presents an efficient face segmentation approach based on face attention model and seeded region merging.A face attention model that jointly exploits the information of skin color and eye's position is first constructed to obtain a facial saliency map,which indicates the position of possible faces and is used to determine seed *** a seeded region merging algorithm based on regional facial saliency is proposed to generate a sequence of regions,and the region with the highest regional facial saliency is selected to represent each *** results on a variety of images demonstrate the good segmentation performance of the proposed face segmentation algorithm.

关键词： face segmentation face attention model seeded region merging

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Face recognition Research Based on Anti-Symmetrical Wavelet and Eigenface

Face Recognition Research Based on Anti-Symmetrical Wavelet ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qian Yin Zhi-Yong Yuan Ying Kong Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science Wuhan University of China Wuhan China School of Computer Science & Technology Beijing Institute of Technology Beijing China

In this paper, a new human face recognition method based on anti-symmetrical biorthogonal wavelet transformation (ASBWT) and eigenface was proposed. First the anti-symmetrical biorthogonal wavelet is chosen to degrade the face image dimension, meanwhile complete the process of face location and segmentation; And then human face is reverted through the face space of eigenface, the traditional average human face is replaced in the within-class scatter matrix. This within-class scatter matrix is used to calculate within-class and between-class distance proportion as a rule function, calculate the twice eigenface through discrete Karhunen-Loeve transform (DKLT), and use singular value decomposition (SVD) method to calculate the eigenvector. Finally we compute the weights and classify the face images. The results show that the proposed method has higher recognition rate and more robust than the traditional eigenface analysis method.

关键词： Face recognition Scattering Matrix decomposition image coding Humans Matrices Degradation Robustness Wavelet analysis Fourier transforms

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Quantification of 3-Dimensional Confluence-Atrial Morphology in Supracardiac Total Anomalous Pulmonary Venous Connection

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JACC: Asia 2024年第8期4卷 594-606页

作者： Shi, Guocheng Huang, Meiping Pei, Yuchen Huang, Peng Wen, Chen Shentu, Jin Zhang, Hao Zhu, Zhongqun Zhong, Yumin Wang, Lisheng Chen, Huiwen Department of Cardiothoracic Surgery Congenital Heart Center Shanghai Children's Medical Center Shanghai Jiao Tong University School of Medicine Department of Catheterization Laboratory Guangdong Cardiovascular Institute Guangdong General Hospital Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University Department of Cardio-Thoracic Surgery Hunan Children's Hospital Changsha Department of Radiology Shanghai Children's Medical Center Shanghai Jiao Tong University School of Medicine

Background: Pulmonary vein stenosis (PVS) continues to be a major complication after surgical repair of total anomalous pulmonary venous connection (TAPVC). Recent studies suggest that the morphology of pulmonary venous confluence and the left atrium (LA) is associated with PVS. However, there are limited data on the prognostic value of integrating quantitative confluence-atrial morphology into risk stratification. Objectives: This study sought to evaluate the prognostic impact of novel imaging metrics derived from 3-dimensional (3D) computed tomography angiography (CTA) modeling on postsurgical PVS (PPVS) in the supracardiac TAPVC (sTAPVC) setting. Methods: Patients undergoing sTAPVC repair in 2017 to 2022 from 3 centers were retrospectively reviewed. Study investigators developed 3D CTA modeled geometric features to quantify confluence-atrial morphology that were analyzed with regard to PPVS. Results: Of the 162 patients (median age 61 days;55% having preoperative pulmonary venous obstruction [prePVO]) included, 47 (29%) with PPVS at a median of 1.5 months ([quartile 1-quartile 3: 1.5-3.0 months]). In the univariable analysis, the indexed total volume of the LA and confluence (iTVLC) and the ratio of the corresponding confluence length to the mean distance between the LA and confluence (CCL/mDBLC ratio) were significantly associated with PPVS. In a multivariable model adjusting for prePVO and age, the iTVLC and CCL/mDBLC ratio independently predicted PPVS (HR: 1.15;95% CI: 1.06-1.25;and HR: 1.20;95% CI: 1.08-1.35, respectively, all P < 0.01). Specifically, an iTVLC ≥20 cm³/m² and a CCL/mDBLC ratio ≥7.7 were significantly associated with a reduced risk of PPVS. Conclusions: Quantification of 3D confluence-atrial morphology appears to offer a deeper and better metric to predict PPVS in patients with sTAPVC. © 2024 The Authors

关键词： 3-dimensional computed tomography congenital heart disease pulmonary vein stenosis total anomalous pulmonary venous connection

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Impulse noise removal using linear prediction model

Impulse noise removal using linear prediction model

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4th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, ITELSIKS 1999

作者： Prudyus, Ivan Voloshynovskiy, Sviatoslav Rytsar, Yuriy Holotyak, Taras Radio Engineering Faculty State University Lvivska Polytechnika 12 S.Bandery Str. Lviv 290646 Ukraine Coordinated Science Laboratory University of Illinois College of Engineering 1308 West Main Street Urbana IL 61801-2307 United States Department of Image Processing and Pattern Recognition Institute of Physics and Mechanics National Academy of Science of Ukraine 5 Naukova str. Lviv Ukraine

ISBN: (纸本)078035768X

Noise removal is an important problem in many applications. In this paper a new two-step scheme of the decision-based impulse noise removal method by means of contaminated pixel detection is proposed and comparison with direct order statistic filtering is given. The proposed methods satisfy both objective and subjective image quality. © 1999 IEEE.

关键词： Impulse noise

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Vehicle Routing Problem with Time Windows using Hybrid Metaheuristic Dragonfly Algorithm and Variable Neighborhood Search: Work on Progress 11

Vehicle Routing Problem with Time Windows using Hybrid Metah...

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11th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024

作者： Yunita, Yunita Stiawan, Deris Rini, Dian Palupi Sriwijaya University Faculty of Computer Science Indonesia Sriwijaya University Intelligent System Research Group Faculty of Computer Science South Sumatera Palembang Indonesia Sriwijaya University Communication Network and Information Security Research Group Faculty of Computer Science South Sumatera Palembang Indonesia Sriwijaya University Image Processing Dan Pattern Recognition Laboratory Group Faculty of Computer Science South Sumatera Palembang Indonesia

ISBN: (纸本)9798350355314

One of the problems with Smart Transportation is the problem of cost and travel time. This problem is known as the Variable Routing Problem (VRP). In some real cases, in addition to considering route selection, there are limitations on the capacity and time period for the vehicle to serve each customer known as Time Windows, so VRP has developed into Variable Routing Problem with Time Windows (VRPTW). One way to solve VRPTW is to use metaheuristic methods. However, the metaheuristic method has a weakness, which are it can get stuck in local optimums and fail to find better global solutions. To overcome this, a combination with other methods or known as hybrid is needed. The formulation of this research problem is how to develop a Smart transportation model using a metaheuristic hybrid algorithm. The purpose of this study is to develop a Smart transportation model using a metaheuristic hybrid algorithm. The method used is to combine two metaheuristic algorithms, which are the Dragonfly Algorithm (DA) and the Variable Neighborhood Search (VNS). The result of this research is a new algorithm model which is a hybrid between DA and VNS. Through a combination of global exploration using DA and local exploitation using VNS, this algorithm is expected to be able to find a better solution and faster convergence in solving VRPTW problems © 2024 IEEE.

关键词： Travel time

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Mining top-K Frequent and Flexible pattern from sequences

Mining top-K Frequent and Flexible Pattern from sequences

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IEEE Conference Anthology

作者： Zhang Junyan Min Fan University Key Laboratory of Pattern Recognition and Intelligent information Processing Chengdu Sichuan Province China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

pattern Mining is a popular issue in biological sequence analysis. With the introduction of wildcard gaps, more interesting patterns can be mined. In this paper, we propose a new definition related to pattern frequency, under which the Apriori property holds. We define a pattern mining problem called Ming top-K Frequent patterns (MFP), where gaps are mined instead of specified. Compared with existing problems, MFP does not require any domain knowledge of the user. However, theoretical analysis and experimental results show that MFP favors inflexible patterns. We then define another problem where the flexibility threshold of each gap is specified by the user. The problem is called Mining top-K Frequent and Flexible patterns (MF 2 P). We develop algorithm with polynomial complexities for both problems. patterns can grow from both sides. Some interesting biological patterns mined by our algorithms are discussed.

关键词： constraints pattern mining sequence wildcard gap

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Patch-based Object Tracking via Locality-constrained Linear Coding

Patch-based Object Tracking via Locality-constrained Linear ...

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第35届中国控制会议

作者： Kunqi Gu Mingna Liu Tao Zhou Fanghui Liu Xiangjian He Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai Institute of Spaceflight Control Technology Infrared Detection Technology Research and Development Center China Aerospace Science and Technology Corporation School of Computing and Communications University of Technology The Key Laboratory of Ministry of Education for System Control and Information Processing

ISBN: (纸本)9781509009107

In this paper,the Locality-constrained Linear Coding(LLC) algorithm is incorporated into the object tracking ***,we extract local patches within a candidate and then utilize the LLC algorithm to encode these *** on these codes,we exploit pyramid max pooling strategy to generate a richer feature *** feature histogram which integrates holistic and part-based features can be more discriminative and ***,an occlusion handling strategy is utilized to make our tracker more ***,an efficient graph-based manifold ranking algorithm is exploited to capture the relevance between target templates and *** tracking,target templates are taken as labeled nodes while target candidates are taken as unlabeled nodes,and the goal of tracking is to search for the candidate that is the most relevant to existing labeled nodes by manifold ranking *** on challenging video sequences have demonstrated the superior accuracy and robustness of the proposed method in comparison to other state-of-the-art baselines.

关键词： object tracking LLC pyramid max-pooling local appearance model manifold ranking

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A New Circle Targets Extraction Algorithm

A New Circle Targets Extraction Algorithm

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The First International Conference on Multimedia Information Networking and Security(第一届国际多媒体网络信息安全会议 MINES 2009)

作者： Chen Zhong Deng He Wang Guoyou Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Multi-Spectral Information Processing State Key Laboratory Wuhan P.R.China

According to the drawback of the traditional circle target extraction algorithm used by Hough Transform, such as computation complexity, low efficiency and etc, an new circle target extraction algorithm is proposed in this paper which can extract multiple circle targets with different radius at one time. First, the Average Absolute Difference is implemented to enhance the edge of the circle targets and suppress the noise of the background; Second, the locally self-adaptive segmentation algorithm is implemented to obtain the binary image. Thirdly, the thinning algorithm is implanted to obtain the single pixel edge of the circle targets and in order to reduce the computation times in the following process, a pruning algorithm is necessary; finally, a modified Hough transform algorithm is proposed to obtain the circle targets. The new circle targets have three advantages: low time consuming, high detection rate, robust to noise and fragmentary boundaries. The experimental results demonstrate that the new algorithm can extract the multiple circle targets quickly and accurately.

关键词： circle extraction hough transformation Average Absolute Difference thinning

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