LEADER 01152nam 2200349Ia 450 001 996385501703316 005 20200824132820.0 035 $a(CKB)4940000000080117 035 $a(EEBO)2264198058 035 $a(OCoLC)ocm13111334e 035 $a(OCoLC)13111334 035 $a(EXLCZ)994940000000080117 100 $a19860205d1669 uy | 101 0 $alat 135 $aurbn||||a|bb| 200 10$aDe viscerum structura exercitatio anatomica$b[electronic resource] /$fMarcelli Malpighii ... ; accedit dissertatio ejusdem de polypo cordis 210 $aLondini $cTypis T.R. Impensis Jo. 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Pandora Sicilia s.r.l. 082 04$a820.9 100 1 $aWheeler, Michael$0166390 245 10$aHeaven, hell, and the Victorians /$cMichael Wheeler 260 $aCambridge :$bCambridge university press,$c1994 300 $aXV, 279 p. ;$c23 cm 650 4$aLetteratura inglese$ySec. 19.$xStoria e critica 650 4$aTeologia dotrinale$zGran Bretagna$ySec. 19. 650 4$aMorte$xAspetti religiosi 650 4$aCristianesimo$xStoria$ySec. 19. 907 $a.b12454928$b02-04-14$c13-11-03 912 $a991003643019707536 945 $aLE012 820.9 WHE$g1$i2012000162822$lle012$o-$pE0.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i12883529$z13-11-03 945 $aLE012 820.9 WHE 1/A$g2$i2012000346529$lle012$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i1473333x$z23-04-08 996 $aHeaven, hell, and the Victorians$9178885 997 $aUNISALENTO 998 $ale012$b13-11-03$cm$da $e-$feng$guik$h0$i1 LEADER 06520nam 22007575 450 001 9910483311603321 005 20251113182619.0 010 $a3-319-10599-X 024 7 $a10.1007/978-3-319-10599-4 035 $a(CKB)3710000000227386 035 $a(SSID)ssj0001338665 035 $a(PQKBManifestationID)11770397 035 $a(PQKBTitleCode)TC0001338665 035 $a(PQKBWorkID)11345523 035 $a(PQKB)10128457 035 $a(DE-He213)978-3-319-10599-4 035 $a(MiAaPQ)EBC6302273 035 $a(MiAaPQ)EBC5586602 035 $a(Au-PeEL)EBL5586602 035 $a(OCoLC)889236741 035 $a(PPN)180626310 035 $a(EXLCZ)993710000000227386 100 $a20140814d2014 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aComputer Vision -- ECCV 2014 $e13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VI /$fedited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (XXVI, 832 p. 351 illus.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v8694 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-319-10598-1 327 $aAll-In-Focus Synthetic Aperture Imaging -- Photo Uncrop -- Solving Square Jigsaw Puzzles with Loop Constraints -- Geometric Calibration of Micro-Lens-Based Light-Field Cameras Using Line Features -- Spatio-temporal Matching for Human Detection in Video -- Collaborative Facial Landmark Localization for Transferring Annotations Across Datasets -- Facial Landmark Detection by Deep Multi-task Learning -- Joint Cascade Face Detection and Alignment -- Weighted Block-Sparse Low Rank Representation for Face Clustering in Videos -- Crowd Tracking with Dynamic Evolution of Group Structures -- Tracking Using Multilevel Quantizations -- Occlusion and Motion Reasoning for Long-Term Tracking -- MEEM: Robust Tracking via Multiple Experts Using Entropy Minimization -- Robust Motion Segmentation with Unknown Correspondences -- Monocular Multiview Object Tracking with 3D Aspect Parts -- Modeling Blurred Video with Layers -- Efficient Image and Video Co-localization with Frank-Wolfe Algorithm -- Non-parametric Higher-Order Random Fields for Image Segmentation -- Co-Sparse Textural Similarity for Interactive Segmentation -- A Convergent Incoherent Dictionary Learning Algorithm for Sparse Coding -- Free-Shape Polygonal Object Localization -- Interactively Guiding Semi-Supervised Clustering via Attribute-Based Explanations -- Attributes Make Sense on Segmented Objects -- Towards Transparent Systems: Semantic Characterization of Failure Modes -- Orientation Covariant Aggregation of Local Descriptors with Embeddings -- Similarity-Invariant Sketch-Based Image Retrieval in Large Databases -- Discovering Object Classes from Activities -- Weakly Supervised Object Localization with Latent Category Learning -- Food-101 ? Mining Discriminative Components with Random Forests -- Latent-Class Hough Forests for 3D Object Detection and Pose Estimation -- FPM: Fine Pose Parts-Based Model with 3D CAD Models -- Learning High-Level Judgments of Urban Perception -- CollageParsing: Nonparametric Scene Parsing by Adaptive Overlapping Windows -- Discovering Video Clusters from Visual Features and Noisy Tags -- Category-Specific Video Summarization -- Assessing the Quality of Actions -- HiRF: Hierarchical Random Field for Collective Activity Recognition in Videos -- Part Bricolage: Flow-Assisted Part-Based Graphs for Detecting Activities in Videos -- GIS-Assisted Object Detection and Geospatial Localization -- Context-Based Pedestrian Path Prediction -- Sliding Shapes for 3D Object Detection in Depth Images -- Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model -- PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding -- Unfolding an Indoor Origami World -- Joint Semantic Segmentation and 3D Reconstruction from Monocular Video -- A New Variational Framework for Multiview Surface Reconstruction -- Multi-body Depth-Map Fusion with Non-intersection Constraints -- Shape from Light Field Meets Robust PCA -- Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval -- ReverseTraining: An Efficient Approach for Image Set Classification -- Real-Time Exemplar-Based Face Sketch Synthesis -- Domain-Adaptive Discriminative One-Shot Learning of Gestures. 330 $aThe seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions. 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v8694 606 $aComputer vision 606 $aPattern recognition systems 606 $aArtificial intelligence 606 $aComputer graphics 606 $aComputer Vision 606 $aAutomated Pattern Recognition 606 $aArtificial Intelligence 606 $aComputer Graphics 615 0$aComputer vision. 615 0$aPattern recognition systems. 615 0$aArtificial intelligence. 615 0$aComputer graphics. 615 14$aComputer Vision. 615 24$aAutomated Pattern Recognition. 615 24$aArtificial Intelligence. 615 24$aComputer Graphics. 676 $a006.37 702 $aFleet$b David$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPajdla$b Tomas$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSchiele$b Bernt$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTuytelaars$b Tinne$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483311603321 996 $aComputer Vision -- ECCV 2014$92587608 997 $aUNINA