01198nam0 2200289 i 450 SUN005255420140707111120.218978-03-87293-17-220090318d2006 |0engc50 baengUS|||| |||||Time series analysis and its applicationswith R examplesRobert H. Shumway, David S. Stoffer2nd edNew YorkSpringerc2006XIII, 575 p.graf.24 cm.001SUN00367912001 *Springer texts in statistics210 New YorkSpringer1985-.Statistica e informatica applicata all'economia e alla statisticaSGSUNC029781USNew YorkSUNL000011Shumway, Robert H.SUNV054038249361Stoffer, David S.SUNV054039254812SpringerSUNV000178650ITSOL20200921RICASUN0052554UFFICIO DI BIBLIOTECA DEL DIPARTIMENTO DI SCIENZE POLITICHE JEAN MONNET04CONS V.C.c.4 04OMA19 20090403 Time series analysis and its applications627543UNICAMPANIA03968nam 22006615 450 99646615850331620200629130539.03-540-47287-810.1007/3-540-55798-9(CKB)1000000000548885(SSID)ssj0000326204(PQKBManifestationID)11268652(PQKBTitleCode)TC0000326204(PQKBWorkID)10264985(PQKB)11045405(DE-He213)978-3-540-47287-2(PPN)155216023(EXLCZ)99100000000054888520121227d1992 u| 0engurnn|008mamaatxtccrRelational Matching[electronic resource] /by George Vosselman1st ed. 1992.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,1992.1 online resource (X, 18 p.) Lecture Notes in Computer Science,0302-9743 ;628Bibliographic Level Mode of Issuance: Monograph3-540-55798-9 Computer vision and matching -- A classification of matching methods -- Formal description of relational matching -- Problem definition and contributions of the thesis -- Information theory:Selected Topics -- Evaluation of mappings between relational descriptions -- Tree search methods and heuristics -- Relational image and model description -- Evaluation functions for object location -- Strategy and performance of the tree search for object location -- Summary and discussion.Relational matching is a method for finding the best correspondences betweenstructural descriptions. It is widely used in computer vision for the recognition and location of objects in digital images. For this purpose, the digital images and the object models are represented by structural descriptions. The matching algorithm then has to determine which image elements and object model parts correspond. This book is the result of abasic study of relational matching. The book focuses particularly on the evaluation of correspondences. In order to find the best match, one needs a measure to evaluate the quality of a match. The author reviews the evaluation measures that have been suggested over the past few decades and presents a new measure based on information theory. The resulting theorycombines matching strategies, information theory, and tree search methods. For the benefit of the reader, comprehensive introductions are given to all these topics.Lecture Notes in Computer Science,0302-9743 ;628ComputersArtificial intelligencePattern recognitionSoftware engineeringTheory of Computationhttps://scigraph.springernature.com/ontologies/product-market-codes/I16005Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Pattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XModels and Principleshttps://scigraph.springernature.com/ontologies/product-market-codes/I18016Software Engineering/Programming and Operating Systemshttps://scigraph.springernature.com/ontologies/product-market-codes/I14002Computers.Artificial intelligence.Pattern recognition.Software engineering.Theory of Computation.Artificial Intelligence.Pattern Recognition.Models and Principles.Software Engineering/Programming and Operating Systems.004.0151Vosselman Georgeauthttp://id.loc.gov/vocabulary/relators/aut745699BOOK996466158503316Relational Matching2830418UNISA