Josef Kittler – författare

This book constitutes the refereed proceedings of the 12th International Workshop on Multiple Classifier Systems, MCS 2015, held in Günzburg, Germany, in June/July 2015. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.

This book constitutes the refereed proceedings of the 20th Iberoamerican Congress on Pattern Recognition, CIARP 2015, held in Montevideo, Uruguay, in November 2015. The 95 papers presented were carefully reviewed and selected from 185 submissions. The papers are organized in topical sections on applications on pattern recognition;

This book constitutes the refereed proceedings of the 9th International Conference on Articulated Motion and Deformable Objects, AMDO 2016, held in Palma de Mallorca, Spain, in July 2016.The 20 papers presented were carefully reviewed and selected from 34 submissions. 3D human reconstruction and recognition;

This book constitutes the refereed proceedings of the 10th International Conference on Articulated Motion and Deformable Objects, AMDO 2018, held in Palma de Mallorca, Spain, in July 2018. The 12 papers presented were carefully reviewed and selected from 26 submissions. 3D human reconstruction and recognition;

Pattern recognition is traditionally considered to cover all aspects of sensory data perception ranging from data acquisition, through preprocessing and low level analysis, to high level interpretation. Owing to its breadth and important application potential, the field of pattern recognition has been attracting considerable attention of researchers in academia and industry and consequently it has been witnessing a rapid growth and perpetual development. The need for dissemination of the latest results is being served by a host of international conferences on pattern recognition. One such series of meetings is regularly held in the United Kingdom under the auspices of the British Pattern Recognition Association. This volume contains papers presented at the BPRA 4th International Conference on Pattern Recognition held in Cambridge, March 28-30, 1988. Alongside the conventional topics of statistical and syntactic pattern recognition, contributions address issues in the hot subject areas of adaptive learning networks, computer vision, knowledge base methods and architectures for pattern processing, and among others, report progress in the application domains of document processing, speech and text recognition and shape analysis for industrial robotics. It is believed that the collection is not merely a report on current activities but that it will also be an important source of inspiration for future developments in the field of pattern recognition.

This book constitutes the refereed proceedings of the 5th International Workshop on Multiple Classifier Systems, MCS 2004, held in Cagliari, Italy in June 2004.The 35 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections on bagging and boosting, combination methods, design methods, performance analysis, and applications.

The belief that a committee of people make better decisions than any individual is widely held and appreciated. We also understand that, for this to be true, the members of the committee have to be simultaneously competent and comp- mentary. This intuitive notion holds true for committees of data sources (such as sensors) and models (such as classi?ers). The substantial current research in the areas of data fusion and model fusion focuses on ensuring that the di?- ent sources provide useful information but nevertheless complement one another to yield better results than any source would on its own. During the 1990s, a variety of schemes in classi?er fusion, which is the focus of this workshop, were developed under many names in di?erent scienti?c communities such as machine learning, pattern recognition, neural networks, and statistics. The previous ?ve workshops on Multiple Classi?er Systems (MCS) were themselves exercises in information fusion, with the goal of bringing the di?erent scienti?c commu- ties together, providing each other with di?erent perspectives on this fascinating topic, and aiding cross-fertilization of ideas. These ?ve workshops achieved this goal, demonstrating signi?cant advances in the theory, algorithms, and appli- tions of multiple classi?er systems. Followingits?vepredecessorspublishedbySpringer,thisvolumecontainsthe proceedings of the 6th International Workshop on Multiple Classi?er Systems (MCS2005)heldattheEmbassySuitesinSeaside,California,USA,June13-15, 2005. Forty-two papers were selected by the Scienti?c Committee, and they were organized into the following sessions: Boosting, Combination Methods, Design of Ensembles, Performance Analysis, and Applications.

This book constitutes the refereed proceedings of the 4th International Conference on Audio-and Video-Based Biometric Person Authentication, AVBPA 2003, held in Guilford, UK in June 2003.The 39 revised full plenary papers and 72 revised full poster papers were carefully reviewed and selected for presentation. There are topical sections on face; speech; fingerprint; image,video processing, and tracking; general issues; handwriting, signature, and palm; gait; and fusion

This book constitutes the refereed proceedings of the Second International Workshop on Multiple Classifier Systems, MCS 2001, held in Cambridge, UK in July 2001. The 44 revised papers presented were carefully reviewed and selected for presentation. The book offers topical sections on bagging and boosting, MCS design methodology, ensemble classifiers, feature spaces for MCS, MCS in remote sensing, one class MCS and clustering, and combination strategies.

Morethanadecadeago,combiningmultipleclassi?erswasproposedasap- siblesolutiontotheproblemsposedbythetraditionalpatternclassi?cation approachwhichinvolvedselectingthebestclassi?erfromasetofcandidates basedontheirexperimentalevaluation. Asnoclassi?erisknowntobethebest forallcasesandtheselectionofthebestclassi?erforagivenpracticaltaskis verydi?cult,diverseresearchcommunities,includingMachineLearning,N- ralNetworks,PatternRecognition,andStatistics,addressedtheengineering problemofhowtoexploitthestrengthswhileavoidingtheweaknessesofd- ferentdesigns. Thisambitiousresearchtrendwasalsomotivatedbyempirical observationsaboutthecomplementarityofdi?erentclassi?erdesigns,natural requirementsofinformationfusionapplications,andintrinsicdi?cultiesasso- atedwiththeoptimalchoiceofsomeclassi?erdesignparameters,suchasthe architectureandtheinitialweightsforaneuralnetwork. Afteryearsofresearch, thecombinationofmultipleclassi?ershasbecomeawellestablishedandexciting researcharea,whichprovidese?ectivesolutionstodi?cultpatternrecognition problems. Aconsiderablebodyofempiricalevidencesupportsthemeritof- signingcombinedsystemswhoseaccuracyishigherthanthatofeachindividual classi?er,andvariousmethodsforthegenerationandthecombinationofm- tipleclassi?ershavebecomeavailable. However,despitetheprovedutilityof multipleclassi?ersystems,nogeneralanswertotheoriginalquestionaboutthe possibilityofexploitingthestrengthswhileavoidingtheweaknessesofdi?erent classi?erdesignshasyetemerged. Otherfundamentalissuesarealsoamatterof on-goingresearchindi?erentresearchcommunities. Theresultsachievedd- ingthepastyearsarealsospreadoverdi?erentresearchcommunities,andthis makesitdi?culttoexchangesuchresultsandpromotetheircross-fertilization. Theacknowledgmentofthefundamentalrolethatthecreationofacommon internationalforumforresearchersofthediversecommunitiescouldplayfor theadvancementofthisresearch?eldmotivatedthepresentseriesofwo- shopsonmultipleclassi?ersystems. Followingitspredecessors,MultipleCl- si?erSystems2000(SpringerISBN3-540-67704-6)and2001(SpringerISBN 3-540-42284-6),thisvolumecontainstheproceedingsoftheThirdInternational WorkshoponMultipleClassi?erSystems(MCS2002),heldattheGrandHotel ChiaLaguna,Cagliari,Italy,onJune24-26,2002. The29papersselectedby thescienti?ccommitteehavebeenorganizedinsessionsdealingwithbagging andboosting,ensemblelearningandneuralnetworks,combinationstrategies, designmethodologies,analysisandperformanceevaluation,andapplications.Theworkshopprogramandthisvolumeareenrichedwiththreeinvitedtalks givenbyJoydeepGhosh(UniversityofTexas,USA),TrevorHastie(Stanford University,USA),andSarunasRaudys(VilniusGediminasTechnicalUniversity, Lithuania). Papersweresubmittedfromresearchersofthefourdiversecom- nities,socon?rmingthatthisseriesofworkshopscanbecomeacommonforum VI Foreword forexchangingviewsandreportinglatestresearchresults. Asfortheprevious editions,thesigni?cantnumberofpapersdealingwithrealpatternrecognition applicationsareproofofthepracticalutilityofmultipleclassi?ersystems. This workshopwassupportedbytheUniversityofCagliari,Italy,theUniversityof Surrey,Guildford,UnitedKingdom,andtheDepartmentofElectricalandEl- tronicEngineeringoftheUniversityofCagliari. Allthesesupportsaregratefully acknowledged. WealsothanktheInternationalAssociationforPatternRecog- tionanditsTechnicalCommitteeTC1onStatisticalPatternRecognitionTe- niquesforsponsoringMCS2002. Wewishtoexpressourappreciationtoallthose whohelpedtoorganizeMCS2002. Firstofall,wewouldliketothankallthe membersoftheScienti?cCommitteewhoseprofessionalismwasinstrumental increatingaveryinterestingtechnicalprogram.Specialthanksareduetothe membersoftheOrganizingCommittee,GiorgioFumera,GiorgioGiacinto,and GianLucaMarcialisfortheirindispensablecontributionstotheMCS2002web sitemanagement,localorganization,andproceedingspreparation. April2002 FabioRoliandJosefKittler WorkshopChairs F. Roli(Univ. ofCagliari,Italy) J. Kittler(Univ. ofSurrey,UnitedKingdom) Scienti?cCommittee J. A. Benediktsson(Iceland) M. Kamel(Canada) H. Bunke(Switzerland) L. I. Kuncheva(UK) L. P. Cordella(Italy) L. Lam(HongKong) B. V. Dasarathy(USA) D. Landgrebe(USA) R. P. W. Duin(TheNetherlands) Dar-ShyangLee(USA) C. Furlanello(Italy) D. Partridge(UK) J. Ghosh(USA) A. J. C. Sharkey(UK) T. K. Ho(USA) K. Tumer(USA) S. Impedovo(Italy) G. Vernazza(Italy) N. Intrator(Israel) T. Windeatt(UK) A. K. Jain(USA) LocalCommittee G. Fumera(Univ. ofCagliari,Italy) G. Giacinto(Univ. ofCagliari,Italy) G. L. Marcialis(Univ. ofCagliari,Italy) Organizedby Dept. ofElectricalandElectronicEngineeringoftheUniversityofCagliari UniversityofSurrey Sponsoredby UniversityofCagliari UniversityofSurrey Dept. ofElectricalandElectronicEngineeringoftheUniversityofCagliari TheInternationalAssociationforPatternRecognition Supportedby UniversityofCagliari Dept. ofElectricalandElectronicEngineeringoftheUniversityofCagliari UniversityofSurrey TableofContents InvitedPapers Multiclassi?erSystems:BacktotheFuture...1 J. Ghosh SupportVectorMachines,KernelLogisticRegressionandBoosting...16 J. Zhu,T. Hastie MultipleClassi?cationSystemsintheContextofFeatureExtractionand Selection...27 ? S. Raudys BaggingandBoosting BoostedTreeEnsemblesforSolvingMulticlassProblems...42 T. Windeatt,G. Ardeshir DistributedPastingofSmallVotes...52 N. V. Chawla,L. O. Hall,K. W. Bowyer,T. E. Moore,Jr. , W. P. Kegelmeyer BaggingandBoostingfortheNearestMeanClassi?er:E?ectsofSample SizeonDiversityandAccuracy...62 M. Skurichina,L. I. Kuncheva,R. P. W. Duin HighlightingHardPatternsviaAdaboostWeightsEvolution ...72 B. Caprile,C. Furlanello,S. Merler UsingDiversitywithThreeVariantsofBoosting:Aggressive,Conservative, andInverse ...81 L. I. Kuncheva,C. J. Whitaker EnsembleLearningandNeuralNetworks MultistageNeuralNetworkEnsembles...91 S. Yang,A. Browne,P. D. Picton ForwardandBackwardSelectioninRegressionHybridNetwork...98 S. Cohen,N. Intrator TypesofMultinetSystem...108 A. J. C.

This book constitutes the refereed proceedings of the 11th Iberoamerican Congress on Pattern Recognition, CIARP 2006, held in Cancun, Mexico in November 2006. The 99 revised full papers presented together with three keynote articles were carefully reviewed and selected from 239 submissions. The papers cover ongoing research and mathematical methods.

Many theoretical and experimental studies have shown that a multiple classi?er system is an e?ective technique for reducing prediction errors [9,10,11,20,19]. These studies identify mainly three elements that characterize a set of cl- si?ers: -Therepresentationoftheinput(whateachindividualclassi?erreceivesby wayofinput). -Thearchitectureoftheindividualclassi?ers(algorithmsandparametri- tion). - The way to cause these classi?ers to take a decision together. Itcanbeassumedthatacombinationmethodise?cientifeachindividualcl- si?ermakeserrors'inadi?erentway',sothatitcanbeexpectedthatmostofthe classi?ers can correct the mistakes that an individual one does [1,19]. The term 'weak classi?ers' refers to classi?ers whose capacity has been reduced in some way so as to increase their prediction diversity. Either their internal architecture issimple(e.g.,theyusemono-layerperceptronsinsteadofmoresophisticated neural networks), or they are prevented from using all the information available. Sinceeachclassi?erseesdi?erentsectionsofthelearningset,theerrorcorre- tion among them is reduced. It has been shown that the majority vote is the beststrategyiftheerrorsamongtheclassi?ersarenotcorrelated.Moreover, in real applications, the majority vote also appears to be as e?cient as more sophisticated decision rules [2,13]. Onemethodofgeneratingadiversesetofclassi?ersistoupsetsomeaspect ofthetraininginputofwhichtheclassi?erisrather unstable. In the present paper,westudytwodistinctwaystocreatesuchweakenedclassi?ers;i.e.learning set resampling (using the 'Bagging' approach [5]), and random feature subset selection (using 'MFS', a Multiple Feature Subsets approach [3]). Other recent and similar techniques are not discussed here but are also based on modi?cations to the training and/or the feature set [7,8,12,21].

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. Being the seventh in a well-established series of meetings providing an international forum for the discussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic. From more than 80 submissions, the Programme Committee selected 49 - pers to create an interesting scienti?c programme. The special focus of MCS 2007 was on the application of multiple classi?er systems in biometrics. This part- ular application area exercises all aspects of multiple classi?er fusion, from - tramodal classi?er combination, through con?dence-based fusion, to multimodal biometric systems. The sponsorship of MCS 2007 by the European Union N- work of Excellence in Biometrics BioSecure and in Multimedia Understanding through Semantics, Computation and Learning MUSCLE and their assistance in selecting the contributions to the MCS 2007 programme consistent with this theme is gratefully acknowledged.

This book constitutes the refereed proceedings of the 12th Iberoamerican Congress on Pattern Recognition, CIARP 2007, held in Valparaiso, Chile, November 13-16, 2007. The 97 revised full papers presented together with four keynote articles were carefully reviewed and selected from 200 submissions. The papers cover ongoing research and mathematical methods for pattern recognition, image analysis, and applications in areas such as computer vision, robotics, industry and health.

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2009, held at the University of Iceland, Reykjavik, Iceland in June 2009. Being the eighth in a well-established series of meetings providing an inter- tional forum for the discussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural networks,pattern recognition,machine learning and stat- tics) concerned with this research topic. From more than 70 submissions, the Program Committee selected 54 papers to create an interesting scienti?c program. The special focus of MCS 2009 was on the application of multiple classi?er systems in remote sensing. This part- ular application uses multiple classi?ers for raw data fusion, feature level fusion and decision level fusion. In addition to the excellent regular submission in the technical program, outstanding contributions were made by invited speakers Melba Crawford from Purdue University and Zhi-Hua Zhou of Nanjing Univ- sity. Papers of these talks are included in these workshop proceedings. With the workshop’sapplicationfocusbeingonremotesensing,Prof.Crawford’sexpertise in the use of multiple classi?cation systems in this context made the discussions on this topic at MCS 2009 particularly fruitful.

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2010, held at the Nile University, Egypt in April 2010. Being the ninth in a well-established series of meetings providing an international forum for d- cussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural n- works, pattern recognition, machine learning and statistics) concerned with this researchtopic.Frommorethan50submissions,theProgramCommitteeselected 31 papers to create an interesting scienti?c program.Paperswere organizedinto sessionsdealingwithclassi?ercombinationandclassi?erselection,diversity,b- ging and boosting, combination of multiple kernels, and applications. The wo- shopprogramandthisvolumewereenrichedbytwoinvitedtalksgivenbyGavin Brown(University of Manchester,UK), and Friedhelm Schwenker(University of Ulm, Germany). As usual, the workshop would not have been possible without the help of many individuals and organizations.First of all, our thanks go to the members of the MCS 2010 Program Committee, whose expertise and dedication helped us create an interesting event that marks the progressmade in this ?eld overthe last year and aspire to chart its future research. The help of James Field from the University of Surrey, who administered the submitted paper reviews, and of Giorgio Fumera who managed the MCS website deserve a particular mention. Special thanks are due to the members of the Nile University Organizing C- mittee,AhmedSalah,AmiraElBaroudy,EsraaAly,HebaEzzat,NesrineSameh, Rana Salah and Mohamed Zahhar for their indispensable contributions to the registration management, local organization, and proceedings preparation.

The Mexican Conference on Pattern Recognition 2010 (MCPR 2010) was the second event organized by the Mexican Association for Computer Vision, N- rocomputing and Robotics (MACVNR). These conferences provide a forum for exchanging scienti?c results and experiences, sharing new knowledge, and - creasing the cooperation between research groups in pattern recognition and related areas, in Mexico, as well as international cooperation. MCPR 2010 was held in Puebla, Mexico, it was hosted and sponsored by the Computer Science Department of the National Institute of Astrophysics, Optics and Electronics (INAOE), jointly with the Center for Computing Research of the National Polytechnic Institute (CIC-IPN). From 89 full papers submitted, 39(43.8%) were accepted for publication in theseproceedingsandfor presentationattheconference.Thecontributionsor- inated from 20 di?erent countries. The review process was carried out by the Scienti?c Committee, composed of internationally recognized scientists, all - perts in their respective ?elds. The conference bene?ted from the contributions made by the invited spe- ers: Edwin Hancock from the Department of Computer Science, University of York (UK); Guozhu Dong from the Data Mining Research Lab, Department of ComputerScienceandEngineering,WrightStateUniversity(USA);andErnesto Bribiesca Correa from the Department of Computer Science of the Center for Research in Applied Mathematics and Systems of the National Autonomous University of Mexico, IIMAS-UNAM (Mexico).We would like to express our sincere gratitude to the invited speakers.

This book constitutes the refereed proceedings of the 10th International Workshop on Multiple Classifier Systems, MCS 2011, held in Naples, Italy, in June 2011. The 36 revised papers presented together with two invited papers were carefully reviewed and selected from more than 50 submissions. The contributions are organized into sessions dealing with classifier ensembles; trees and forests; one-class classifiers; multiple kernels; classifier selection; sequential combination; ECOC; diversity; clustering; biometrics; and computer security.

This book constitutes the refereed proceedings of the 11th International Workshop on Multiple Classifier Systems, MCS 2013, held in Nanjing, China, in May 2013. The 34 revised papers presented together with two invited papers were carefully reviewed and selected from 59 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.

This book is the outcome of a NATO Advanced Study Institute on Pattern Recog­ nition Theory and Applications held in Spa-Balmoral, Belgium, in June 1986. This Institute was the third of a series which started in 1975 in Bandol, France, at the initia­ tive of Professors K. S. Fu and A. Whinston, and continued in 1981 in Oxford, UK, with Professors K. S. Fu, J. Kittler and L. -F. Pau as directors. As early as in 1981, plans were made to pursue the series in about 1986 and possibly in Belgium, with Professor K. S. Fu and the present editors as directors. Unfortunately, Ie sort en decida autrement: Professor Fu passed away in the spring of 1985. His sudden death was an irreparable loss to the scientific community and to all those who knew him as an inspiring colleague, a teacher or a dear friend. Soon after, Josef Kittler and I decided to pay a small tribute to his memory by helping some of his plans to materialize. With the support of the NATO Scientific Affairs Division, the Institute became a reality. It was therefore but natural that the proceedings of the Institute be dedicated to him. The book contains most of the papers that were presented at the Institute. Papers are grouped along major themes which hopefully represent the major areas of contem­ porary research. These are: 1. Statistical methods and clustering techniques 2. Probabilistic relaxation techniques 3. From Markovian to connectionist models 4.

This 18-volume set constitutes the refereed proceedings of the 8th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2025, held in Shanghai, China, during October 15-18, 2025.The 692 full papers included in this book, comprising 66 oral presentations and 626 posters, were carefully reviewed and selected from 2370 submissions.PRCV's mission is to serve as a comprehensive platform for dialogues among researchers from both the academic field and the industry. While its primary focus is to encourage academic exchange, it also places emphasis on fostering ties between academia and industry, keeping abreast of leading academic innovations and to showcase the most recent research breakthroughs, pioneering thoughts, and advanced techniques in pattern recognition and computer vision.

This 18-volume set constitutes the refereed proceedings of the 8th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2025, held in Shanghai, China, during October 15-18, 2025.The 692 full papers included in this book, comprising 66 oral presentations and 626 posters, were carefully reviewed and selected from 2370 submissions.PRCV's mission is to serve as a comprehensive platform for dialogues among researchers from both the academic field and the industry. While its primary focus is to encourage academic exchange, it also places emphasis on fostering ties between academia and industry, keeping abreast of leading academic innovations and to showcase the most recent research breakthroughs, pioneering thoughts, and advanced techniques in pattern recognition and computer vision.

This 18-volume set constitutes the refereed proceedings of the 8th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2025, held in Shanghai, China, during October 15-18, 2025.The 692 full papers included in this book, comprising 66 oral presentations and 626 posters, were carefully reviewed and selected from 2370 submissions.PRCV's mission is to serve as a comprehensive platform for dialogues among researchers from both the academic field and the industry. While its primary focus is to encourage academic exchange, it also places emphasis on fostering ties between academia and industry, keeping abreast of leading academic innovations and to showcase the most recent research breakthroughs, pioneering thoughts, and advanced techniques in pattern recognition and computer vision.