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Computer Vision Systems - 8th international conference, ICVS 2011, Proceedings

Computer Vision Systems - 8th International Conference, ICVS...

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8th international conference on Computer Vision Systems, ICVS 2011

ISBN: (纸本)9783642239670

The proceedings contain 42 papers. The topics discussed include: knowing what happened - automatic documentation of image analysis processes;efficient use of geometric constraints for sliding-window object detection in video;a method for asteroids 3D surface reconstruction from close approach distances;RT-SLAM: a generic and real-time visual SLAM implementation;a quantitative comparison of speed and reliability for log-polar mapping techniques;toward accurate feature detectors performance evaluation;evaluation of local descriptors for action recognition in videos;on the spatial extents of SIFT descriptors for visual concept detection;an experimental framework for evaluating PTZ tracking algorithms;unsupervised activity extraction on long-term video recordings employing soft computing relations;and unsupervised discovery, modeling, and analysis of long term activities.

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Dynamic pattern of Agricultural Landscapes in Response to Urbanization across Hangzhou Metropolitan Region: A Remote Sensing Approach

Dynamic Pattern of Agricultural Landscapes in Response to Ur...

引用

2011 international conference on Informatics,Cybernetics,and Computer Engineering(ICCE 2011)

作者： Zou Dongdong Jiang Zhi Zhang Qi Zhang Yuan Oujiang College Wenzhou University Physics & Electronic Information Engineering College Wenzhou University College of Environmental & Resources Sciences Zhejiang University Research Center of Remote Sensing & Geoscience Northeast Institute of Geography & Agroecology of CAS

ISBN: (纸本)9783642251870

This paper applied multiple endmember spectral mixture analysis(MESMA) to interpret Landsat satellite imageries and then analyzed the spatiotemporal dynamics of agricultural landscapes within Hangzhou metropolitan *** 1994 and 2003,this region has witnessed accelerated urbanization based on four indicators:total population,percentage of non-agriculture population,GDP per capita,and area of impervious ***,conversion,fragmentation,irregularity and isolation of agricultural landscapes were also captured according to four class-level metrics:total area,patch density,area-weighted mean shape index,and Euclidean nearest neighbor *** showed that increased impervious area was significantly correlated with declined area and configuration of agricultural *** in GDP per capita was also correlated with increased irregularity of agricultural *** of total population and percentage of nonagriculture population were weakly associated with all the agricultural landscape metrics,denoting that the two indicators did not have direct influences on agricultural landscape ***,distance to the nearest road was also a good indicator of how the cultivated land was lost and *** results demonstrated complexities of relationships between urbanization and agricultural landscapes,and highlighted the importance of selected variables,spatiotemporal scales and land-use classification when quantifying these relationships.

关键词： urbanization agriculture indicator landscape pattern change remote sensing

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Off-line signature identification using background and foreground information

Off-line signature identification using background and foreg...

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2011 international conference on Digital Image computing: Techniques and Applications, DICTA 2011

作者： Pal, Srikanta Alireza, Alaei Pal, Umapada Blumenstein, Michael School of Information and Communication Technology Griffith University Gold Coast QLD Australia Department of Studies in Computer Science University of Mysore Mysore 570 006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9780769545882

Biometric systems play an important role in the field of information security as they are extremely required for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is currently receiving renewed interest and is only one of several techniques used to verify the identities of individuals. Signatures provide a secure means for confirmation and authorization in legal documents. So nowadays, signature identification and verification becomes an essential component in automating the rapid processing of documents containing embedded signatures. In this paper, a technique for a bi-script off-line signature identification system is proposed. In the proposed signature identification system, the signatures of English and Bengali (Bangla) are considered for the identification process. Different features such as under sampled bitmaps, modified chain-code direction features and gradient features computed from both background and foreground components are employed for this purpose. Support Vector Machines (SVMs) and Nearest Neighbour (NN) techniques are considered as classifiers for signature identification in the proposed system. A database of 1554 English signatures and 1092 Bengali signatures are used to generate the experimental results. Various results based on different features are calculated and analysed. The highest accuracies of 99.41%, 98.45%;and 97.75% are obtained based on the modified chain-code direction, under-sampled bitmaps and gradient features respectively using 1800 (1100 English+700 Bengali) samples for training and 846 (454 English+392 Bengali) samples for testing. © 2011 IEEE.

关键词： Biometrics

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soft vector quantization with inverse power-function distributions for machine learning applications

Soft vector quantization with inverse power-function distrib...

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international conference on Advances in Intelligent Automation and Systems Engineering

作者： Attia, Mohamed Almazyad, Abdulaziz El-Mahallawy, Mohamed Al-Badrashiny, Mohamed Nazih, Waleed Engineering Company for the Development of Computer System RDI 12613 Giza Egypt Luxor Technologies Inc. Oakville ON L6L6V2 Canada College of Computing and IT Arab Academy for Science and Technology - AAST Heliopolis Campus Cairo Cairo Egypt

ISBN: (纸本)9781461403722

This chapter discusses the positive impact of soft vector quantization on the performance of machine-learning systems that include one or more vector quantization modules. The most impactful gains here are avoiding over-fitting and boosting the robustness of such systems in the presence of considerable parasitic variance;e.g. noise, in the runtime inputs. The chapter then introduces a soft vector quantization scheme with inverse power-function distributions, and analytically derives an upper bound of its relative quantization noise energy to that of typical (hard-deciding) vector quantization. This relative noise is expressed as a closed-form function of the power in order to allow the selection of its optimal values of that compromise both a soft enough vector quantization with a stable performance via small enough relative quantization noise. Finally, we present empirical evidence obtained via experimenting with two versions of the best reported OCR system for cursive scripts - that happened to deploy discrete HMMs - one version with hard vector quantization and the other one with our herein presented soft quantization. Test samples of real-life scanned Arabic text pages are used to challenge both versions;hence the recognition error margins are compared. © 2011 Springer Science+Business Media, LLC.

关键词： Vector quantization

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Electrical consumers data clustering through optimum-path forest

Electrical consumers data clustering through optimum-path fo...

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2011 16th international conference on Intelligent System Applications to Power Systems, ISAP 2011

作者： Ramos, Caio C. O. Souza, André N. Nakamura, Rodrigo Y. M. Papa, João P. Department of Electrical Engineering University of São Paulo São Paulo São Paulo Brazil Department of Computing UNESP - Univ. Estadual Paulista Bauru São Paulo Brazil

Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.

关键词： pattern recognition

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New lower bounds for two multicolor vertex Folkman numbers

New lower bounds for two multicolor vertex Folkman numbers

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international conference on Computer and Management

作者： Shao, Zehui Liang, Meilian He, Jiandong Xu, Xiaodong School of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province China School of Mathematics and Information Science Guangxi University Nanning 530004 China Guangxi Academy of Sciences Nanning 530007 China

For a graph G, G → (a1, a2, · · ·, ar)v means that in every r-coloring of the vertices in G, there exists a monochromatic ai-clique of color i for some i∈{1, 2, · · ·, r}. The vertex Fo... 详细信息

ISBN: (纸本)9781424492831

For a graph G, G → (a1, a2, · · ·, ar)v means that in every r-coloring of the vertices in G, there exists a monochromatic ai-clique of color i for some i∈{1, 2, · · ·, r}. The vertex Folkman number is defined as Fv(a1, a2, ···, ar;k) = min{|V(G)|: G → (a1, a2, ···, ar)v and Kk G}. In general, computing lower and upper bounds for vertex Folkman numbers is difficult. In this note, based on theoretical analysis and computation, we show that Fv(2, 3, 3;4) ≥ 19 and Fv(3, 3, 3;4) ≥ 24, and suggest a cyclic graph of order 91 which may give an upper bound for Fv(3, 3, 3;4). ©2011 IEEE.

关键词： Graph theory

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Feature Selection for Mobility pattern recognition in Mobile Ad-Hoc Networks

Feature Selection for Mobility Pattern Recognition in Mobile...

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international conference on Wireless Communications, Networking and Mobile computing (WiCom)

作者： S. M. Mousavi Faculty of Computer Engineering University of Qom Qom Iran

Mobility is one of the most challenging issues in mobile Ad-Hoc networks which has significant impact on performance of variety of network protocols. To deal with this matter the protocol designers should be able to analyze movement behavior of mobile nodes in a particular wireless network. In our previous works we have proposed a simple mobility pattern recognition method which can classify mobility traces into different mobility model classes. The main issue here is finding appropriate features which can classify different mobility traces into mobility classes accurately. In this paper we try to introduce suitable and minimal features to make our mobility pattern recognition method able to distinguish and classify different mobility models more accurate. Simulation results show significant efficiency of our proposed mobility pattern recognition method using appropriate feature sets introduces in this paper.

关键词： Mobile communication Measurement Ad hoc networks Mobile computing Markov processes Feature extraction pattern recognition

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SIGAda 2011 - Proceedings of the 2011 ACM international conference on Ada and Related Technologies

SIGAda 2011 - Proceedings of the 2011 ACM International Conf...

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2011 Annual international conference of the Association for computing Machinery's Special Interest Group on the Ada Programming Language, SIGAda 2011

ISBN: (纸本)9781450310284

The proceedings contain 10 papers. The topics discussed include: how to measure and optimize reliable embedded software;service-oriented architecture (SOA) concepts and implementations;improving quality of Ada software with range analysis;SF1: introduction to Ada;designing and checking coding standards for Ada;building embedded real-time applications;a parallel programming model for Ada;stack safe parallel recursion with paraffin;how to make Ada go viral;software vulnerabilities precluded by SPARK;enhancing SPARK's contract checking facilities using symbolic execution;an Ada design pattern recognition tool for AADL performance analysis;improving quality of Ada software with range analysis;making the non-executable ACATS tests executable;and DO-178C: the next avionics safety standard.

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Advancements in Arabic-to-English hierarchical machine translation

Advancements in Arabic-to-English hierarchical machine trans...

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15th international conference of the European Association for Machine Translation, EAMT 2011

作者： Huck, Matthias Vilar, David Stein, Daniel Ney, Hermann Human Language Technology and Pattern Recognition Group RWTH Aachen University Germany DFKI GmbH Berlin Germany

ISBN: (纸本)9789081486118

In this paper we study several advanced techniques and models for Arabic-to-English statistical machine translation. We examine how the challenges imposed by this particular language pair and translation direction can be successfully tackled within the framework of hierarchical phrase-based translation. We extend the state-of-the-art with a novel cross-system and cross-paradigm lightlysupervised training approach. In addition, for following recently developed techniques we provide a concise review, an empirical evaluation, and an in-depth analysis: soft syntactic labels, a discriminative word lexicon model, additional reorderings, and shallow rules. We thus bring together complementary methods that previously have only been investigated in isolation and mostly on different language pairs. Combinations of the methods yield significant improvements over a baseline using a usual set of models. The resulting hierarchical systems perform competitive on the large-scale NIST Arabic-to-English translation task. © 2011 European Association for Machine Translation.

关键词： Hierarchical systems

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Dynamic Successive Feed-Forward Neural Network for Learning Fuzzy Decision Tree

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13th international conference on Rough Sets, Fuzzy Sets and Granular computing (RSFDGrC)

作者： Singh, Manu Pratap Dr BR Ambedkar Univ Dept Comp Sci ICIS Agra Uttar Pradesh India

ISBN: (纸本)9783642218804;9783642218811

Fuzzy decision trees have been substantiated to be a valuable tool and more efficient than neural networks for pattern recognition task due to some facts like computation in making decisions are simpler and important features can be selected automatically during the design process. Here we present a feed forward neural network which learns fuzzy decision trees during the descent along the branches for its classification. Every decision instances of decision tree are represented by a node in neural network. The neural network provides the degree of membership of each possible move to the fuzzy set << good move >> corresponding to each decision instance. These fuzzy values constitute the core of the probability of selecting the move out of the set of the children of the current node. This results in a natural way for driving the sharp discrete-state process running along the decision tree by means of incremental methods on the continuous-valued parameters of the neural network. A simulation program in C has been deliberated and developed for analyzing the consequences. The effectiveness of the learning process is tested through experiments with three real-world classification problems.

关键词： Decision tree pattern classification fuzzy system artificial neural networks fuzzy logic

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