LEADER 00753nam0-22002531i-450 001 990002594130403321 005 20230329131157.0 010 $a0-8240-5329-X 035 $a000259413 035 $aFED01000259413 035 $a(Aleph)000259413FED01 035 $a000259413 100 $a20000920d1982----km-y0itay50------ba 101 0 $aeng 200 1 $aStandardized accountancy in Germany with a new appendix$fdi SINGER H. W. 210 $aNew York$cGarland Publishing$d1982 700 1$aSinger,$bH.W.$0368726 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002594130403321 952 $aDEP-PLT11-02-RA$b1608 DEA$fECA 959 $aECA 996 $aStandardized accountancy in Germany with a new appendix$93060912 997 $aUNINA LEADER 01100nam a22002771i 4500 001 991002088579707536 005 20030405143942.0 008 030925s1969 xxu|||||||||||||||||eng 035 $ab12240424-39ule_inst 035 $aARCHE-028804$9ExL 040 $aBiblioteca Interfacoltà$bita$cA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l. 082 04$a387 100 1 $aGee, Joshua$0452351 245 14$aThe trade and navigation of Great-Britain /$cconsidered by Joshua Gee 260 $aNew York :$bA. M. Kelley,$c1969 300 $aXXXIX, 239 p. ;$c23 cm 440 0$aReprints of economic classics 500 $aRipr. della 4. ed. / London : A. Bettesworth ; C. Hitch ; S. Birth, 1738. 650 4$aGran Bretagna$xCommercio 650 4$aGran Bretagna$xNavigazione 907 $a.b12240424$b02-04-14$c08-10-03 912 $a991002088579707536 945 $aLE002 Dir. VI A 38$g1$i2002000040534$lle002$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i12624639$z08-10-03 996 $aTrade and navigation of Great-Britain$9153996 997 $aUNISALENTO 998 $ale002$b08-10-03$cm$da $e-$feng$gxxu$h4$i1 LEADER 04494nam 22006015 450 001 9910337576903321 005 20200630071138.0 010 $a3-030-04040-2 024 7 $a10.1007/978-3-030-04040-6 035 $a(CKB)4100000007335016 035 $a(DE-He213)978-3-030-04040-6 035 $a(MiAaPQ)EBC5628152 035 $a(PPN)233798854 035 $a(EXLCZ)994100000007335016 100 $a20190101d2019 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHierarchical Perceptual Grouping for Object Recognition $eTheoretical Views and Gestalt-Law Applications /$fby Eckart Michaelsen, Jochen Meidow 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (XI, 195 p. 100 illus., 9 illus. in color.) 225 1 $aAdvances in Computer Vision and Pattern Recognition,$x2191-6586 311 $a3-030-04039-9 327 $aIntroduction -- Reflection Symmetry -- Good Continuation in Rows or Frieze Symmetry -- Rotational Symmetry -- Closure ? Hierarchies of Gestalten -- Search -- Illusions -- Prolongation in Good Continuation -- Parallelism and Rectangularity -- Lattice Gestalten -- Primitive Extraction -- Knowledge and Gestalt Interaction -- Learning -- Appendix A: General Adjustment Model with Constraints. 330 $aThis unique text/reference presents a unified approach to the formulation of Gestalt laws for perceptual grouping, and the construction of nested hierarchies by aggregation utilizing these laws. The book also describes the extraction of such constructions from noisy images showing man-made objects and clutter. Each Gestalt operation is introduced in a separate, self-contained chapter, together with application examples and a brief literature review. These are then brought together in an algebraic closure chapter, followed by chapters that connect the method to the data ? i.e., the extraction of primitives from images, cooperation with machine-readable knowledge, and cooperation with machine learning. Topics and features: Offers the first unified approach to nested hierarchical perceptual grouping Presents a review of all relevant Gestalt laws in a single source Covers reflection symmetry, frieze symmetry, rotational symmetry, parallelism and rectangular settings, contour prolongation, and lattices Describes the problem from all theoretical viewpoints, including syntactic, probabilistic, and algebraic perspectives Discusses issues important to practical application, such as primitive extraction and any-time search Provides an appendix detailing a general adjustment model with constraints This work offers new insights and proposes novel methods to advance the field of machine vision, which will be of great benefit to students, researchers, and engineers active in this area. Dr.-Ing. Eckart Michaelsen is a researcher at the Object Recognition Department of Fraunhofer IOSB, Ettlingen, Germany. Dr.-Ing. Jochen Meidow is a researcher at the Scene Analysis Department of the same institution. 410 0$aAdvances in Computer Vision and Pattern Recognition,$x2191-6586 606 $aPattern perception 606 $aRemote sensing 606 $aArchitecture 606 $aGroup theory 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aRemote Sensing/Photogrammetry$3https://scigraph.springernature.com/ontologies/product-market-codes/J13010 606 $aArchitecture, general$3https://scigraph.springernature.com/ontologies/product-market-codes/K0000X 606 $aGroup Theory and Generalizations$3https://scigraph.springernature.com/ontologies/product-market-codes/M11078 615 0$aPattern perception. 615 0$aRemote sensing. 615 0$aArchitecture. 615 0$aGroup theory. 615 14$aPattern Recognition. 615 24$aRemote Sensing/Photogrammetry. 615 24$aArchitecture, general. 615 24$aGroup Theory and Generalizations. 676 $a006.4 676 $a006.4 700 $aMichaelsen$b Eckart$4aut$4http://id.loc.gov/vocabulary/relators/aut$01060300 702 $aMeidow$b Jochen$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910337576903321 996 $aHierarchical Perceptual Grouping for Object Recognition$92512317 997 $aUNINA