LEADER 01596nas a2200385 i 4500 001 991002773829707536 005 20231109125612.0 008 150603c19809999it mx p 0 b0ita d 022 $a0394-7149 035 $ab14230264-39ule_inst 040 $aBibl. Dip.le Aggr. DiSTeBA - Sez. Biologia$beng 041 0 $aita$aeng$aspa 082 00$a594.005$222 210 0 $aBoll. malacol. 229 00$aBollettino malacologico 245 00$aBollettino malacologico :$bpubblicazione mensile edita dalla Unione malacologica italiana. 260 $aMilano :$bUnione malacologica italiana ;$c1980- 300 $a v. :$bill. ;$c24 cm 310 $aMonthly (irregular) 362 1 $aBegan with: Anno 16, n. 1/2 (genn.-feb. 1980) 546 $aChiefly in Italian; some also in English and Spanish 550 $aIssued by: Unione malacologica italiana in the year 1982 ; Società italiana di malacologia from 1983 to 1989 592 $aLE003 Fondo Parenzan 1980-1982; lac.: 1980-1982; 650 0$aMollusks$vPeriodicals 710 2 $aUnione malacologica italiana 710 2 $aSocietà italiana di malacologia 770 0 $aBollettino malacologico. Supplemento$x1121-4155 770 0 $tNotiziario S.I.M. 780 00$tBollettino malacologico della Unione malacologica italiana$x0394-7130 907 $a.b14230264$b03-06-15$c03-06-15 912 $a991002773829707536 945 $aLE003 (Fondo Parenzan)$g1$lle003$og$pE0.00$rn$s- $t18$u0$v0$w0$x0$y.i15678933$z03-06-15 996 $aBollettino malacologico$9255124 997 $aUNISALENTO 998 $ale003$b03-06-15$cs$da $fita$git $h0$i0 LEADER 01619nam 2200409Ia 450 001 9910696998003321 005 20250409163020.0 035 $a(CKB)5470000002382907 035 $a(OCoLC)521128839 035 $a(OCoLC)521117614 035 $a(EXLCZ)995470000002382907 100 $a20100219d2007 ua 0 101 0 $aeng 181 $ctxt$2rdacontent 182 $ch$2rdamedia 183 $ahe$2rdacarrier 200 00$aBaghouse filtration products $eSouthern Filter Media, LLC, PE-16/M-SPES filter sample /$fprepared by RTI International, ETS, Incorporated 210 1$aResearch Triangle Park, NC :$cU.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, Air Polluiton Prevention and Control Division,$d[2007] 215 $axiii, 8 pages $cillustrations ;$d28 cm 225 1 $aEnvironmental technology verification report 300 $a"February 2007." 300 $a"EPA cooperative agreement CR 831911-01." 300 $aFormat not distributed to depository libraries. 320 $aIncludes bibliographical references (page 8). 410 0$aEnvironmental technology verification report. 517 $aBaghouse filtration products 606 $aAir filters 615 0$aAir filters. 712 02$aRTI International. 712 02$aETS, Incorporated. 712 02$aNational Risk Management Research Laboratory (U.S.).$bAir Pollution Prevention and Control Division. 801 0$bGPO 801 1$bGPO 906 $aBOOK 912 $a9910696998003321 996 $aBaghouse filtration products$93455430 997 $aUNINA LEADER 07672nam 22008655 450 001 9910484682603321 005 20251226202510.0 010 $a3-540-88682-6 024 7 $a10.1007/978-3-540-88682-2 035 $a(CKB)1000000000490443 035 $a(SSID)ssj0000316921 035 $a(PQKBManifestationID)11231522 035 $a(PQKBTitleCode)TC0000316921 035 $a(PQKBWorkID)10287115 035 $a(PQKB)11094552 035 $a(DE-He213)978-3-540-88682-2 035 $a(MiAaPQ)EBC3063531 035 $a(MiAaPQ)EBC6511630 035 $a(Au-PeEL)EBL6511630 035 $a(OCoLC)1110933648 035 $a(PPN)130185868 035 $a(EXLCZ)991000000000490443 100 $a20100301d2008 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aComputer Vision - ECCV 2008 $e10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part I /$fedited by David Forsyth, Philip Torr, Andrew Zisserman 205 $a1st ed. 2008. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2008. 215 $a1 online resource (XXXVII, 801 p.) 225 1 $aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v5302 300 $aIncludes index. 311 08$a3-540-88681-8 320 $aIncludes bibliographical references and index. 327 $aLecture by Prof. Jan Koenderink -- Something Old, Something New, Something Borrowed, Something Blue -- Recognition -- Learning to Localize Objects with Structured Output Regression -- Beyond Nouns: Exploiting Prepositions and Comparative Adjectives for Learning Visual Classifiers -- Learning Spatial Context: Using Stuff to Find Things -- Segmentation and Recognition Using Structure from Motion Point Clouds -- Poster Session I -- Keypoint Signatures for Fast Learning and Recognition -- Active Matching -- Towards Scalable Dataset Construction: An Active Learning Approach -- GeoS: Geodesic Image Segmentation -- Simultaneous Motion Detection and Background Reconstruction with a Mixed-State Conditional Markov Random Field -- Semidefinite Programming Heuristics for Surface Reconstruction Ambiguities -- Robust Optimal Pose Estimation -- Learning to Recognize Activities from the Wrong View Point -- Joint Parametric and Non-parametric Curve Evolution for Medical Image Segmentation -- Localizing Objects with Smart Dictionaries -- Weakly Supervised Object Localization with Stable Segmentations -- A Perceptual Comparison of Distance Measures for Color Constancy Algorithms -- Scale Invariant Action Recognition Using Compound Features Mined from Dense Spatio-temporal Corners -- Semi-supervised On-Line Boosting for Robust Tracking -- Reformulating and Optimizing the Mumford-Shah Functional on a Graph ? A Faster, Lower Energy Solution -- Viewpoint Invariant Pedestrian Recognition with an Ensemble of Localized Features -- Perspective Nonrigid Shape and Motion Recovery -- Shadows in Three-Source Photometric Stereo -- Hamming Embedding and Weak Geometric Consistency for Large Scale Image Search -- Estimating Geo-temporal Location of Stationary Cameras Using Shadow Trajectories -- An Experimental Comparison of Discrete and Continuous Shape Optimization Methods -- Image Feature Extraction Using Gradient Local Auto-Correlations -- Analysis of Building Textures for Reconstructing Partially Occluded Facades -- NonrigidImage Registration Using Dynamic Higher-Order MRF Model -- Tracking of Abrupt Motion Using Wang-Landau Monte Carlo Estimation -- Surface Visibility Probabilities in 3D Cluttered Scenes -- A Generative Shape Regularization Model for Robust Face Alignment -- Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs -- VideoCut: Removing Irrelevant Frames by Discovering the Object of Interest -- ASN: Image Keypoint Detection from Adaptive Shape Neighborhood -- Online Sparse Matrix Gaussian Process Regression and Vision Applications -- Multi-stage Contour Based Detection of Deformable Objects -- Brain Hallucination -- Range Flow for Varying Illumination -- Some Objects Are More Equal Than Others: Measuring and Predicting Importance -- Robust Multiple Structures Estimation with J-Linkage -- Human Activity Recognition with Metric Learning -- Shape Matching by Segmentation Averaging -- Search Space Reduction for MRF Stereo -- Estimating 3D Face Model and Facial Deformation from a Single Image Based on Expression Manifold Optimization -- 3D Face Recognition by Local Shape Difference Boosting -- Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing -- Recovering Light Directions and Camera Poses from a Single Sphere -- Tracking with Dynamic Hidden-State Shape Models -- Interactive Tracking of 2D Generic Objects with Spacetime Optimization -- A Segmentation Based Variational Model for Accurate Optical Flow Estimation -- Similarity Features for Facial Event Analysis -- Building a Compact Relevant Sample Coverage for Relevance Feedback in Content-Based Image Retrieval -- Discriminative Learning for Deformable Shape Segmentation: A Comparative Study -- Discriminative Locality Alignment -- Stereo -- Efficient Dense Scene Flow from Sparse or Dense Stereo Data -- Integration of Multiview Stereo and Silhouettes Via Convex Functionals on Convex Domains -- Using Multiple Hypotheses to Improve Depth-Maps for Multi-View Stereo -- Sparse Structures in L-Infinity Norm Minimization for Structure and Motion Reconstruction. 330 $aThe four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction. . 410 0$aImage Processing, Computer Vision, Pattern Recognition, and Graphics,$x3004-9954 ;$v5302 606 $aData mining 606 $aComputer vision 606 $aImage processing$xDigital techniques 606 $aComputer graphics 606 $aPattern recognition systems 606 $aDigital humanities 606 $aData Mining and Knowledge Discovery 606 $aComputer Vision 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aComputer Graphics 606 $aAutomated Pattern Recognition 606 $aDigital Humanities 615 0$aData mining. 615 0$aComputer vision. 615 0$aImage processing$xDigital techniques. 615 0$aComputer graphics. 615 0$aPattern recognition systems. 615 0$aDigital humanities. 615 14$aData Mining and Knowledge Discovery. 615 24$aComputer Vision. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aComputer Graphics. 615 24$aAutomated Pattern Recognition. 615 24$aDigital Humanities. 676 $a006.37 702 $aForsyth$b David 702 $aTorr$b P. H. S. 702 $aZisserman$b Andrew 712 12$aEuropean Conference on Computer Vision. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484682603321 996 $aComputer Vision – ECCV 2008$9774090 997 $aUNINA