曹先彬
信息安全,智能计算等。
个性化签名
- 姓名:曹先彬
- 目前身份:
- 担任导师情况:
- 学位:
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学术头衔:
博士生导师, 教育部“新世纪优秀人才支持计划”入选者
- 职称:-
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学科领域:
发酵工程
- 研究兴趣:信息安全,智能计算等。
曹先彬,博士,中国科学技术大学计算机系教授,博士生导师。1969年生。1996年获中国科学技术大学智能信息处理专业博士学位。研究方向包括行人检测系统、计算智能、信息安全等。现为中国科学技术大学计算机科学技术系主任助理,人工智能研究中心副主任,安徽省计算与通讯软件重点实验室常务副主任,中国通信学会青年工作委员会委员。至今已主持了10多项国家自然科学基金、863、973子课题等科研项目及多个省部级科研项目,并作为技术负责人或骨干参与了多项国家自然科学基金、863、973等课题的研究;在国内外主要学术刊物和学术会议上已发表论文90余篇。2000年获安徽省科技进步二等奖,2004年获安徽省科技进步三等奖、2005年获安徽省优秀学术论文二等奖。
2005年入选首届“安徽省优秀中青年学术带头人计划”,2007年入选“教育部新世纪优秀人才计划”。
主要研究方向:信息安全,智能计算等。
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主页访问
1110
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关注数
0
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成果阅读
537
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成果数
14
【期刊论文】A Low-Cost Pedestrian-Detection SystemWith a Single Optical Camera
曹先彬, Xian-Bin Cao, Hong Qiao, Senior Member, IEEE, and John Keane
,-0001,():
-1年11月30日
The ultimate purpose of a pedestrian-detectionsystem (PDS) is to reduce pedestrian-vehicle-related injury. Mostsuch systems tend to adopt expensive sensors, such as infrareddevices, in expectation of better performance. In comparison, alow-cost optical-camera-based system has much potential practicalvalue, including a greater detection range, and can easily betrained to detect other objects. However, such low-cost systems aredifficult to design (e.g., little original information can be collected,and the scene is very complex). To address these problems, aneffective and reliable classifier is needed. The classifier should havea proper structure, its features need to be well selected, and a largenumber of high-quality samples are necessary for training. In thispaper, we present a low-cost PDS which only uses a single opticalcamera. We design a cascade classifier to achieve an effective andreliable detection. First, our system scans two sequential framesat each zoom scale with a sliding window. Second, with eachwindow, both appearance and motion features are extracted. Awell-trained cascade classifier, combining statistical learning witha decomposed support-vector-machine classifier, then determineswhether the window contains a human body. At the same time,to provide as much information as possible about the pedestrian,a small-scale weighted template tree trained by a coevolutionaryalgorithm is adopted to identify each pedestrian’s direction, andthe distance of each from the vehicle is also provided using anestimation algorithm. During the training procedure, we select keyfeatures by using the AdaBoost algorithm and a large numberof high-quality samples. Experimental results demonstrate thatthe system is suitable for pedestrian detection in city traffic: Thedetection speed is more than 10 ft/s, the detection rate reaches80%, and the false positive rate is no more than 0.3‰.
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67浏览
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189下载
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【期刊论文】COEVOLUTIONARY OPTIMIZATION ALGORITHM WITH DYNAMICSUB-POPULATION SIZE
曹先彬, Yuanping Guo, Xianbin Cao and Hongzhang Yin Zeying Tang
,-0001,():
-1年11月30日
This paper proposes a coevolutionary optimization algorithm called DCOA.DCOA mainly focuses on how to adjust sub-population size self-adaptively so as to improvethe optimizing performance. To achieve this, a strategy is introduced which consistsof three rules: internal competition, external competition and spontaneous growthrules. These rules can control individual reproduction and elimination speed in each subpopulation.Furthermore, the adjustment can be proven globally asymptotically stable. Inthe experiments, we compare the performances of DCOA, macroevolutionary algorithm(MA) [13] and simple genetic algorithm (SGA) with typical test functions. The resultsshow that DCOA is able to find the global optimum on most difficult functions, nothingless than MA which uses simulated annealing technique. At the same time, DCOA convergesquickly, similar to SGA and faster than MA.
Coevolutionary optimization algorithm,, Dynamic population size,, Globalasymptotic stability
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42浏览
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120下载
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【期刊论文】Negative selection based immune optimization
曹先彬, Xianbin Cao a, b, Hong Qiao c, *, Yanwu Xu a
Advances in Engineering Software 38(2007)649-656,-0001,():
-1年11月30日
An immune optimization algorithm is proposed in this paper based on the immune negative selection. The algorithm NSIOA is motivatedby the negative selection mechanism in biological immune recognition. Different from the existing immune optimization methods,NSIOA constantly removes the worst solutions to get the optimal solution. Considering that removal of poor members of a populationmight lead to the loss of design information that may actually help identify better solutions in the search space, the proposed NSIOA isdesigned to keep the diversity of antibodies while removing poor members, therefore the algorithm will converge to global optimalsolution with high probability. The convergence property and the complexity of the algorithm have also been analyzed. To illustratethe efficiency of the algorithm is used in solving the travel salesman problem. The theoretical analysis and experimental results show thatthe algorithm is of a strong potential in solving practical problems.
Immune algorithm, Optimization, Negative selection, Travel salesman problem
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75浏览
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162下载
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【期刊论文】A New Strategy of Dynamically Adjusting Population Size forCoevolutionary Algorithms
曹先彬, XianBin CAO, YuanPing GUO and Hong QIAO
,-0001,():
-1年11月30日
How to dynamically adjust population size is one ofthe most important research topics in coevolutionary computation.This paper proposes a new strategy to dynamically adjustpopulation size during a coevolutionary process. Three factors areconsidered in the strategy to describe the influence on populationsize. They are the natural growth of sub-populations, the internalcompetition of individuals from same sub-population and theinteraction between individuals from different sub-populations. Itis proven that the proposed strategy is globally asymptoticallystable and also the convergence of a coevolutionary algorithm withthe strategy is investigated. Finally, the behavior of the proposedstrategy in practical use is illustrated.
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41浏览
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99下载
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【期刊论文】An Optimized Hierarchical Classifier for PedestrianDetection*
曹先彬, Yanwu Xu, Xianbin Cao Hong Qiao
,-0001,():
-1年11月30日
Classification is an essential technology inPedestrian Detection System (PDS). Until now, single-classifierand basic cascaded classifier had been widely used in PDS;however, most of them can hardly satisfy the 3 requirements atthe same time: high detection speed, high detection rate and lowfalse positive rate. In this paper, we proposed an optimizedhierarchical classifier which can satisfy the 3 requirements. Theproposed method adopted Corse-to-fine and Early-rejectionprinciples to achieve global high performance. It consists of twohierarchies, the first one is used to quickly reject non-pedestrianobjects and select out only a few candidates; the second onemakes further verification to these candidates. Furthermore,each hierarchy was optimized with statistical models basing onexperiments; and each hierarchy is a treelike classifier which hasspecific optimization demands. At last, an overall performanceevaluation standard is proposed, and the experimental resultsshowed that the proposed classifier had better overallperformance.
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36浏览
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99下载
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【期刊论文】Pedestrian Detection with Local Feature Assistant
曹先彬, Y.W. Xu, X. B. Cao H. Qiao
,-0001,():
-1年11月30日
Until now, existing pedestrian detection systemsusually use global features (e.g. appearance or motion) of humanbody to detect pedestrian; however, the detection rate needs to beimproved in many situations since sometimes the global featurescan not be obtained. For example, a pedestrian may be partlycovered by a car or his/her part may hide into the background.Therefore it is essential to adopt some local features of key partsof human body to assist pedestrian detection.In this paper, we propose a method using some key localfeatures of human body to help pedestrian detection. Since theintroduction of additional features will cost the system more time,in order to ensure the detection speed, we firstly use bothappearance and motion global features of human body to selectcandidates, and then use local features of head and leg to dofurther confirmation. In the confirmation stage, we use threekinds of local features (head appearance, face color and haircolor) to detect the head of each candidate; at the same time, wealso choose some particular local appearance features to detectthe leg. The experimental results indicate that this method canimprove detection rate with almost the same detection speed;additionally, it can reduce false alarm sometimes.
edestrian detection,, Local feature,, AdaBoost algorithm
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44浏览
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44下载
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【期刊论文】Co-Evolution based Feature Selection for PedestrianDetection
曹先彬, Y. P. Guo*t, X. B. Cao*t, Y. W. Xu*t and Q. Hongt
,-0001,():
-1年11月30日
In a pedestrian detection system, the most criticalrequirement is to quickly and reliably determine whether acandidate region contains a pedestrian. The detection ability ofwhole system determines directly upon quality of chosen features.However, due to the large number and various types of availablefeatures, it is difficult to find an optimal feature subset andacquire the proper feature proportion at the same time formost traditional methods including AdaBoost Algorithm. Thispaper presents a co-evolutionary method with sub-population sizeadjusting strategy for the feature selection problem in pedestriandetection system. Our method is able to find an optimal featuresubset and adjust feature proportion to a proper state in themean time. Experiments show that our method performs betterthan AdaBoost Algorithm.
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36浏览
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48下载
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【期刊论文】Modeling the Evolution of Web using Vertex Content Similarity
曹先彬, Jing Ma, Xianbin Cao, Yuanping Guo
,-0001,():
-1年11月30日
In the evolution process of World Wide Web, contentsof web pages play important roles because of their directeffect on linking preference. In this paper, we propose amodel which combines vertex connectivity and content similarityin a proportional manner. Analytical solutions indicatethat our model exhibits a power-law degree distributionwith variable exponent determined by the weight ofcontent similarity. Distribution of content similarity on connectedvertex pairs shows content similar web pages trendto be linked together. Simulation results show our modelyields remarkably agreements of both degree and contentsimilarity distributions with real network.
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30浏览
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53下载
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【期刊论文】How Contents Influence Clustering Features in the Web
曹先彬, Xueqi Cheng, Fuxin Ren
,-0001,():
-1年11月30日
In World Wide Web, contents of web documents play importantroles in the evolution process because of their effectson linking preference. A majority of topological propertiesare content-related, and among them the clusteringfeatures are sensitive to contents of Web documents. In thispaper, we first observe the impacts of content similarity onweb links by introducing a metric called Linkage Probability.Then we investigate how contents influence the formationmechanism of the most basic cluster, triangle, with ametric named Triangularization Probability. Experimentalresults indicate that content similarity has a positive functionin the process of cluster formation in theWeb. Theoreticalanalysis predicts the contents influence on the clusteringfeatures in the Web very well.
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28浏览
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60下载
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【期刊论文】A Low-Cost Pedestrian Detection System with a SingleOptical Camera*
曹先彬, Y.W. Xu, X.B. Cao H. Qiao
,-0001,():
-1年11月30日
This paper presents a low-cost solution forpedestrian detection using a single optical video camera on amoving vehicle. Since only one optical camera can collect just alittle original information, our system scan two sequential framesto get both appearance and motion information. We use zoomimage and slide window techniques to select the objective region,apply a cascaded classifier combined with statistical learning andSVMto recognize human body, adopt zoom-scale to estimate thedistance from a pedestrian and develop a Distance Transformalgorithm to forecast his/her orientation. This system is suitablefor detecting pedestrians in the range of 0.3-20 meters in the citytraffic with the speed under 50km/h. The test with videos of realcity traffic indicates that our system has got acceptable detectingrate and processing speed.
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29浏览
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74下载
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