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1. |
Record Nr. |
UNISA996202530503316 |
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Titolo |
Computer Vision -- ECCV 2014 [[electronic resource] ] : 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VII / / edited by David Fleet, Tomas Pajdla, Bernt Schiele, Tinne Tuytelaars |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
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ISBN |
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Edizione |
[1st ed. 2014.] |
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Descrizione fisica |
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1 online resource (XXVI, 632 p. 261 illus.) |
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Collana |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics ; ; 8695 |
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Disciplina |
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Soggetti |
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Optical data processing |
Pattern recognition |
Artificial intelligence |
Computer graphics |
Image Processing and Computer Vision |
Pattern Recognition |
Artificial Intelligence |
Computer Graphics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di contenuto |
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Person Re-Identification Using Kernel-Based Metric Learning Methods -- Saliency in Crowd -- Webpage Saliency -- Deblurring Face Images with Exemplars -- Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution -- Hybrid Image Deblurring by Fusing Edge and Power Spectrum Information -- Affine Subspace Representation for Feature Description -- A Generative Model for the Joint Registration of Multiple Point Sets -- Change Detection in the Presence of Motion Blur and Rolling Shutter Effect -- An Analysis of Errors in Graph-Based Keypoint Matching and Proposed Solutions -- OpenDR: An Approximate Differentiable Renderer -- A Superior Tracking Approach: Building a Strong Tracker through Fusion -- |
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Training-Based Spectral Reconstruction from a Single RGB Image -- On Shape and Material Recovery from Motion -- Intrinsic Image Decomposition Using Structure-Texture Separation and Surface Normals -- Multi-level Adaptive Active Learning for Scene Classification -- Graph Cuts for Supervised Binary Coding -- Planar Structure Matching under Projective Uncertainty for Geolocation -- Active Deformable Part Models Inference -- Simultaneous Detection and Segmentation -- Learning Graphs to Model Visual Objects across Different Depictive Styles -- Analyzing the Performance of Multilayer Neural Networks for Object Recognition -- Learning Rich Features from RGB-D Images for Object Detection and Segmentation -- Scene Classification via Hypergraph-Based Semantic Attributes Subnetworks Identification -- OTC: A Novel Local Descriptor for Scene Classification -- Multi-scale Orderless Pooling of Deep Convolutional Activation Features -- Expanding the Family of Grassmannian Kernels: An Embedding Perspective -- Image Tag Completion by Noisy Matrix Recovery -- ConceptMap: Mining Noisy Web Data for Concept Learning -- Shrinkage Expansion Adaptive Metric Learning -- Salient Montages from Unconstrained Videos -- Action-Reaction: Forecasting the Dynamics of Human Interaction -- Creating Summaries from User Videos -- Spatiotemporal Background Subtraction Using Minimum Spanning Tree and Optical Flow -- Robust Foreground Detection Using Smoothness and Arbitrariness Constraints -- Video Object Co-segmentation by Regulated Maximum Weight Cliques -- Dense Semi-rigid Scene Flow Estimation from RGBD Images -- Video Pop-up: Monocular 3D Reconstruction of Dynamic Scenes -- Joint Object Class Sequencing and Trajectory Triangulation (JOST) -- Scene Chronology. |
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Sommario/riassunto |
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The 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. |
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2. |
Record Nr. |
UNINA9910821371103321 |
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Autore |
Windt Anna |
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Titolo |
Naturwissenschaftliches Experimentieren Im Elementarbereich : Evaluation verschiedener Lernsituationen / / Anna Windt |
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Pubbl/distr/stampa |
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Berlin : , : Logos, , 2011 |
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ISBN |
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Descrizione fisica |
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1 online resource (400 pages) : illustrations |
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Collana |
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Studien zum Physik- und Chemielernen |
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Disciplina |
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Soggetti |
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Science - Study and teaching |
Science - Study and teaching - Evaluation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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PublicationDate: 20111130 |
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Sommario/riassunto |
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Long description: Bei der Entwicklung von Bildungsangeboten in den Naturwissenschaften geht seit einigen Jahren der Trend wieder zu einer Vermittlung naturwissenschaftlicher Inhalte an Kinder im Elementarbereich. Eine zentrale Arbeitsweise ist dabei das Experimentieren. Das Ziel der vorliegenden Untersuchung war es, Aussagen über die Wirkung des naturwissenschaftlichen Experimentierens auf die Kompetenzen von Vorschulkindern zu gewinnen. Dabei wurden drei verschiedene Lernsituationen realisiert, die sich im Grad der Selbstständigkeit der Kinder und in der Rolle der Erzieherin voneinander unterschieden. In der ersten Lernsituation experimentierten die Kinder täglich unter Anleitung einer Erzieherin, die das Vorgehen der Kinder strukturierte. In der zweiten Lernsituation experimentierten die Kinder selbstständig und die Erzieherin stand als Ansprechpartnerin bereit. In der dritten Lernsituation wechselten die beiden Angebote täglich. Die Untersuchung zeigt zum einen, dass Vorschulkinder grundsätzlich in der Lage sind, durch das naturwissenschaftliche Experimentieren Kompetenzen zu erwerben. Zum anderen zeigt der Vergleich der Lernsituationen, dass Vorschulkinder dafür eine Anleitung durch eine Erzieherin benötigen, die allerdings nicht täglich erfolgen muss. An der Hauptuntersuchung waren zwölf Kindertageseinrichtungen im Raum Dortmund mit |
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insgesamt 221 Vorschulkindern beteiligt. |
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