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A Survey on Statistical pattern Feature Extraction

引用

4th international conference on Intelligent Computing

作者： Ding, Shifei Jia, Weikuan Su, Chunyang Jin, Fengxiang Shi, Zhongzhi China Univ Min & Technol Sch Comp Sci & Technol Xuzhou 221008 Peoples R China Acad Sinica Key Lab Intelligent Informat Proc Inst Comop Technol Beijing 100080 Peoples R China Agr Univ Coll Plant Protection Tai An Shandong 271018 Peoples R China Shandong Univ Sci Technol Coll Geoinformation Sci Engn Qingdao 266510 Peoples R China

ISBN: (纸本)9783540859833

the goal of statistical pattern feature extraction (SPFE) is 'low loss dimension reduction'. As the key link of pattern recognition, dimension reduction has become the research hot spot and difficulty in the fields of pattern recognition, machine learning, data mining and so on. pattern feature extraction is one of the most challenging research fields and has attracted the attention from many scholars. this paper summarily introduces the basic principle of SPFE, and discusses the latest progress of SPFE from the aspects such as classical statistical theories and their modifications, kernel-based methods, wavelet analysis and its modifications, algorithms integration and so on. At last we discuss the development trend of SPFE.

关键词： Extraction

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Detecting and Tracing DDoS attacks by Intelligent Decision Prototype

Detecting and Tracing DDoS attacks by Intelligent Decision P...

引用

6th IEEE international conference on Pervasive Computing and Communications

作者： Chonka, Ashley Zhou, Wanlei Singh, Jaipal Xiang, Yang Deakin Univ Sch Engn & Informat Technol Geelong Vic 3220 Australia Cent Queensland Univ Sch Management & Informat Rockhampton Qld 4702 Australia

ISBN: (纸本)9781424442362

Over the last couple of months a large number of Distributed Denial of Service (DDoS) attacks have occurred across the world, especially targeting those who provide web services. IP traceback a counter measure against DDoS, is the ability to trace IP packets back to the true source/s of the attack. In this paper, an IP traceback scheme using a machine learning technique called Intelligent Decision Prototype (IDP), is proposed. IDP can be used on both Probabilistic Packet Marking (PPM) and Deterministic Packet Marking (DPM) traceback schemes to identify DDoS attacks. this will greatly reduce the packets that are marked and in effect make the system more efficient and effective at tracing the source of an attack compared with other methods. IDP can be applied to many security systems such as data mining, Forensic Analysis, Intrusion Detection Systems (IDS) and DDoS defense systems.

关键词： IP Traceback machine learning Decision trees Distributed Denial of Service Intelligent Decision Prototype

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data mining technologies inspired from visual principle 1

引用

5th IFIP international conference on Intelligent Information Processing

作者： Xu, Zongben Xi'an Jiaotong University China

ISBN: (数字)9780387876856

ISBN: (纸本)9780387876849

In this talk we review the recent work done by our group on data mining (DM) technologies deduced from simulating visual principle. through viewing a DM problem as a cognition problems and treading a data set as an image with each light point located at a datum position, we developed a series of high efficient algorithms for clustering, classification and regression via mimicking visual principles. In pattern recognition, human eyes seem to possess a singular aptitude to group objects and find important structure in an efficient way. thus, a DM algorithm simulating visual system may solve some basic problems in DM research. From this point of view, we proposed a new approach for data clustering by modeling the blurring effect of lateral retinal interconnections based on scale space theory. In this approach, as the data image blurs, smaller light blobs merge into large ones until the whole image becomes one light blob at a low enough level of resolution. By identifying each blob with a cluster, the blurring process then generates a family of clustering along the hierarchy. the proposed approach provides unique solutions to many long standing problems, such as the cluster validity and the sensitivity to initialization problems, in clustering. We extended such an approach to classification and regression problems, through combatively employing the Weber's law in physiology and the cell response classification facts. the resultant classification and regression algorithms are proven to be very efficient and solve the problems of model selection and applicability to huge size of data set in DM technologies. We finally applied the similar idea to the difficult parameter setting problem in support vector machine (SVM). Viewing the parameter setting problem as a recognition problem of choosing a visual scale at which the global and local structures of a data set can be preserved, and the difference between the two structures be maximized in the feature space, we derived a di

关键词： data mining

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An improvement on learning with local and global consistency

An improvement on learning with local and global consistency

引用

international conference on pattern recognition

作者： Jie Gui De-Shuang Huang Zhuhong You Department of Automation University of Science and Technology Hefei China Hefei Institute of Intelligent Machines Chinese Academy and Sciences Hefei Anhui China Intelligent Computing Lab Hefei Institute of IntelligentMachines Chinese Academy and Sciences Hefei Anhui China

ISBN: (纸本)9781424421749

A modified version for semi-supervised learning algorithm with local and global consistency was proposed in this paper. the new method adds the label information, and adopts the geodesic distance rather than Euclidean distance as the measure of the difference between two data points when conducting calculation. In addition we add class prior knowledge. It was found that the effect of class prior knowledge was different between under high label rate and low label rate. the experimental results show that the changes attain the satisfying classification performance better than the original algorithms.

关键词： Semisupervised learning learning systems Euclidean distance Automation Level measurement machine learning pattern classification data mining Economic forecasting Inspection

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Classification by bagged consistent itemset rules

Classification by bagged consistent itemset rules

引用

international conference on pattern recognition

作者： Yohji Shidara Mineichi Kudo Atsuyoshi Nakamura Graduate School of Information Science and Technology Hokkaido University Hokkaido Japan

Associative classifiers that utilize association rules have been widely studied. It has been shown that associative classifiers often outperform traditional classifiers. Associative classifiers usually find only rules with high support values, because reducing the minimum support to be satisfied increases computational cost. However, rules with low support but high confidence may contribute to classification. We have proposed an approach to build a classifier composed of almost all consistent (100% confident) rules. the proposed classifier was extended by introducing item reduction and bagging in order to relax the constraint of consistency, which resulted in slightly increased performance for 26 datasets from the UCI machine learning repository.

关键词： Itemsets Bagging Association rules Costs data mining machine learning Radiofrequency interference

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Incremental machine learning techniques for document layout understanding

Incremental machine learning techniques for document layout ...

引用

international conference on pattern recognition

作者： S. Ferilli M. Biba T.M.A. Basile F. Esposito Dipartimento di Informatica Università di Bari

ISBN: (纸本)9781424421749

In real-world digital libraries, artificial intelligence techniques are essential for tackling the automatic document processing task with sufficient flexibility. the great variability in document kind, content and shape requires powerful representation formalisms to catch all the domain complexity. the continuous flow of new documents requires adaptable techniques that can progressively adjust the acquired knowledge on documents as long as new evidence becomes available, even extending if needed the set of recognized document types. Both these issues have not yet been thoroughly studied. this paper presents an incremental first-order logic learning framework for automatically dealing with various kinds of evolution in digital repositories content: evolution in the definition of class definitions, evolution in the set of known classes and evolution by addition of new unknown classes. Experiments show that the approach can be applied to real-world.

关键词： machine learning Software libraries Artificial intelligence Shape data mining learning systems Automatic logic units Production systems Digital systems Technology management

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AICCSA 08 the 6th IEEE/ACS international conference on computer systems and applications

AICCSA 08 The 6th IEEE/ACS international conference on compu...

引用

ACS/IEEE international conference on Computer Systems and Applications

the following topics were dealt with: bioinformatics; computer systems; data mining; wireless networks; MIMO; parallel systems; distributed systems; pattern recognition; image processing; biometrics; computer security...

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Confidence rated boosting algorithm for generic object detection

Confidence rated boosting algorithm for generic object detec...

引用

international conference on pattern recognition

作者： Nayyar A. Zaidi David Suter Department of Electrical and Computer Systems Engineering Monash University Clayton VIC Australia

ISBN: (纸本)9781424421749

In this paper we propose a confidence rated boosting algorithm based on Ada-boost for generic object detection. Confidence rated Ada-boost algorithm has not been applied to generic object detection problem; in that sense our work is novel. We represent images as bag of words, where the words are SIFT descriptors extracted over some interest points. We compare our boosting algorithm to another version of boosting algorithm called Gentle-boost. Our approach generalizes well and performs equal or better than Gentle-boost. We show our results on four categories from the Caltech data sets, in terms of ROC curves.

关键词： Boosting Object detection Object recognition machine learning Systems engineering and theory data mining Face recognition Shape Frequency Histograms

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8. Advanced techniques for face-based biometrics

8. Advanced techniques for face-based biometrics

引用

international conference on pattern recognition

作者： Massimo Tistarelli Universita di Sassari

Face recognition is nowadays one of the most challenging biometric modalities for the identification of individuals. In the last two decades several experimental as well as commercial systems have been developed exploiting different physical properties of the face image. Either being based on processing 2D or 3D information all these methods perform a face classification of the individuals based on some relevant features extracted from the raw image data. the data acquisition, preprocessing and the feature extraction/selection are all topics of the greatest importance to design a good performing recognition system. At the same time, the right choice of the features to be used as the basis for the face representation, which must be based on the uniqueness of such features, as well as most advanced issues such as the incorporation of quality information and the cope for ageing effects, are all of paramount importance. the tutorial will consists of two sessions (half day of total duration) devoted to the description of both the basic and most advanced techniques related to face recognition. the lectures will provide a comprehensive outline of face- based biometrics, its relation to biological systems (the psychophysics of the human visual system), including the existing applications and commercial systems. the lectures will provide an in-depth analysis of the state-of-the-art algorithms for face-image analysis including: face detection and tracking, landmark localization, feature extraction, face representation and classification. the lectures will mainly explore the image processing aspects of the recognition process. As for classification, machine learning algorithms will be also presented, including kernel methods as related to learning and the approximation theory. the most relevant issues and problems will be raised, providing practical solutions and algorithms responding to them. Particular attention will be given to the most advanced and new techniques for face

关键词： Biometrics Face detection Face recognition Feature extraction machine learning algorithms Aging Algorithm design and analysis data mining data acquisition Biological systems

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Sparse Non-negative pattern learning for image representation

Sparse Non-negative Pattern Learning for image representatio...

引用

IEEE international conference on Image Processing

作者： Dian Gong Xuemei Zhao Qiong Yang Department of Electrical Engineering University of California Riverside CA USA Department of Electronics Engineering Tsinghua University Beijing China ESAT-PSI/VISICS Katholieke Universiteit Leuven Heverlee Belgium

In this paper, we propose sparse non-negative pattern learning (SNPL) based on self-taught learning framework. In the algorithm, visual patterns are first learned from unlabeled data by non-negative matrix approximation with sparseness constraints, and then features are extracted by the second part of the algorithm, a conjugate family based non-negative sparse feature extraction method. By combining sparse and non-negative constraints of patterns together, SNPL model gives a better representation for images than state-of-art methods. Beyond that, we give an analytical solution for feature extraction although it is approximate, and thereby we extract the features for self-taught learning framework in a faster and more stable way. We apply the new model to various areas, including pattern coding, feature extraction, and recognition. Experimental results show the advantages of SNPL model.

关键词： Image representation Feature extraction data mining Approximation algorithms Sparse matrices machine learning Principal component analysis Independent component analysis Testing pattern recognition

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