Structural, Syntactic, and Statistical Pattern Recognition [electronic resource] : Joint IAPR International Workshops, SSPR 2006 and SPR 2006, Hong Kong, China, August 17-19, 2006. Proceedings / edited by Dit-Yan Yeung, James T. Kwok, Ana Fred, Fabio Roli, Dick Ridder.Material type: TextLanguage: English Series: Lecture Notes in Computer Science: 4109Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Description: XXI, 939 p. Also available online. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540372417Subject(s): Computer science | Computational complexity | Artificial intelligence | Computer graphics | Computer vision | Optical pattern recognition | Computer Science | Pattern Recognition | Discrete Mathematics in Computer Science | Artificial Intelligence (incl. Robotics) | Computer Graphics | Image Processing and Computer VisionAdditional physical formats: Printed edition:: No titleDDC classification: 006.4 LOC classification: Q337.5TK7882.P3Online resources: Click here to access online
Invited Talks -- SSPR -- Poster Papers -- SPR -- Poster Papers.
This volume in the Springer Lecture Notes in Computer Science (LNCS) series contains 103 papers presented at S+SSPR 2006, which was the ?fth time that the SPR and SSPR workshops organized by Technical Committees TC1 and TC2 of the International Association for Pattern Recognition (IAPR) were held together as joint workshops. It was also the ?rst time that the joint workshops were held in the Far East, at the beautiful campus of the Hong Kong University of Science and Technology (HKUST), on August 17–19, 2006, right before the 18th InternationalConference on PatternRecognition (ICPR 2006),also held in Hong Kong. SPR 2006 and SSPR 2006 together received 217 paper submissions from 33 countries. This volume contains 99 accepted papers, with 38 for oral presen- tion and 61 for poster presentation. In addition to parallel oral sessions for SPR and SSPR, there were also some joint oral sessions with papers of interest to both the SPR and SSPR communities. A recent trend that has emerged in the pattern recognition and machine learning research communities is the study of graph-based methods that integrate statistical and structural approaches. For this reason, a special joint session on graph-based methods was co-organized by Technical Committee TC15 to explore new research issues in this topic. Mo- over,invitedtalkswerepresentedbyfourprominentspeakers:RobertP. W. Duin from Delft Universityof Technology,The Netherlands, winner of the 2006Pierre Devijver Award; Tin Kam Ho from Bell Laboratories of Lucent Technologies, USA; Thorsten Joachims from Cornell University, USA; and B. John Oommen from Carleton University, Canada.