This book constitutes the proceedings of the Second International Workshop on Similarity Based Pattern Analysis and Recognition, SIMBAD 2013, which was held in York, UK, in July 2013. The 18 papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of problems and perspectives, from supervised to unsupervised learning, from generative to discriminative models, from theoretical issues to real-world practical applications, and offer a timely picture of the state of the art in the field.
Edwin R. Hancock Livres





Structural, syntactic, and statistical pattern recognition
- 758pages
- 27 heures de lecture
This volume in the Springer Lecture Notes in Computer Science (LNCS) series features papers from the S+SSPR 2010 Workshops, marking the seventh joint event of the SPR and SSPR workshops. Organized by TC1 and TC2 of the International Association for Pattern Recognition (IAPR), the conference took place in Cesme, Izmir, Turkey, from August 18–20, 2010, shortly before the 20th International Conference on Pattern Recognition (ICPR) in Istanbul. The workshops aim to provide an international forum for presenting the latest results and exchanging ideas in statistical and structural pattern recognition. S+SSPR 2010 received 99 paper submissions from various countries, reflecting a global perspective. This volume includes 70 accepted papers, with 39 for oral and 31 for poster presentations. The event featured parallel sessions for both SPR and SSPR, along with two joint sessions of interest to both communities. To enhance the experience, there were also two joint panel discussions on “Structural Learning” and “Clustering,” which included short presentations followed by discussions. An innovative aspect this year was the filming of the proceedings by Videol- tures.
This book constitutes the refereed proceedings of the 13th IMA International Conference on the Mathematics of Surfaces held in York, UK in September 2009. The papers in the present volume include seven invited papers, as well as 16 submitted papers. The topics covered include subdivision schemes and their continuity, polar patchworks, compressive algorithms for PDEs, surface invariant functions, swept volume parameterization, Willmore flow, computational conformal geometry, heat kernel embeddings, and self-organizing maps on manifolds, mesh and manifold construction, editing, flattening, morphing and interrogation, dissection of planar shapes, symmetry processing, morphable models, computation of isophotes, point membership classification and vertex blends. Surface types considered encompass polygon meshes as well as parametric and implicit surfaces.
Graph based representations in Pattern Recognition
- 271pages
- 10 heures de lecture
This volume contains the papers presented at the Fourth IAPR Workshop on Graph Based Representations in Pattern Recognition. The workshop was held at the King’s Manor in York, England between 30 June and 2nd July 2003. The previous workshops in the series were held in Lyon, France (1997), Haindorf, Austria (1999), and Ischia, Italy (2001). The city of York provided an interesting venue for the meeting. It has been said that the history of York is the history of England. There have been both Roman and Viking episodes. For instance, Constantine was proclaimed emperor in York. The city has also been a major seat of ecclesiastical power and was also involved in the development of the railways in the nineteenth century. Much of York’s history is evidenced by its buildings, and the King’s Manor is one of the most important and attractive of these. Originally part of the Abbey, after the dissolution of the monasteries by Henry VIII, the building became a center of government for the Tudors and the Stuarts (who stayed here regularly on their journeys between London and Edinburgh), serving as the headquarters of the Council of the North until it was disbanded in 1561. The building became part of the University of York at its foundation in 1963. The papers in the workshop span the topics of representation, segmentation, graph-matching, graph edit-distance, matrix and spectral methods, and gra- clustering.
Energy minimization methods in computer vision and pattern recognition
- 331pages
- 12 heures de lecture
C 2 - E C - (EC '99), $ % &, E, % 26 29, 1999. + . + 1997. + % % -,, % . A % %, -, % % % % . 35 % . E % % . B % - 17 % . % . +, -,,, . % % . F, ? % . F, % % . % % %: . C, . D; . D, F. F, . . A . ? % A% % @ - >; C @ . A & % % % ?- @ - F . % B . 1999 E Program Co Chairs E . UniversityofYork, UK UniversityofVenice, Italy Program Committee B INRIA, France B UniversityofBonn, Germany F InstitutoSuperiorTecnico, Portugal D NanyangTechnologicalUniversity, Singapore UniversityofSurrey, UK A YaleUniversity, USA @ McGillUniversity, Canada @ $ TheWeizmannInstituteofScience, Israel > UniversityofNewMexico, USA A >. & Smith KettlewellEyeResearchInstitute, USA INRIA, France @ . YaleUniversity, USA