Exploratory Image Databases: Content-Based Retrieval (Communications, Networking and Multimedia)


Enter the code below and hit Verify. Free Shipping All orders of Don't have an account? Update your profile Let us wish you a happy birthday! Make sure to buy your groceries and daily needs Buy Now. Let us wish you a happy birthday! Exploiting document feature interactions for efficient information fusion in high dimensional spaces.

Automatic image annotation with relevance feedback and latent semantic analysis. Hierarchical long-term learning for automatic image annotation. Clustered multidimensional scaling for exploration in information retrieval. Information Fusion in Multimedia Information Retrieval. Multimedia Retrieval and Classification for Web Content. Visual object categorization with indefinite kernels in discriminantanalysis framework. Performance evaluation of a contextual news story segmentation algorithm.

Dual diffusion model of spreading activation for content-based imageretrieval.

Exploratory Image Databases: Content-Based Retrieval (Communications, Networking and Multimedia)

Benchmarking image and video retrieval: A contextual model for semantic video structuring. Semantic segmentation of video collections using boosted random fields. Countering the false positive projection effect in nonlinear asymmetricclassification. A new framework for handling large multimediacollections. Multimedia autoannotation via hierarchical semantic ensembles. In Proceedings of the Int. Visual object categorization using distance-based discriminant analysis.

Iterative majorization approach to the distance-based discriminantanalysis. Evaluation of distance-based discriminant analysis and its kernelizedextension in visual object recognition.

Content-Based Image Retrieval on Mobile Devices

Managing Video at Large. OWL-based reasoning with retractable inference. Benchmarking Image Retrieval Applications. Towards Meeting Information Sytems: Overview of approaches to semantic augmentation of multimedia databasesfor efficient access and content retrieval. Extension to the Multimedia Retrieval Markup Language: A communicationprotocol for content-based image retrieval.

A framework for benchmarking in visual information retrieval. Video shot detection based on temporal linear prediction of motion. Video structuring, indexing and retrieval based on global motionwavelet coefficients. Construction of a Formal Multimedia Benchmark. Past, Present and Future. A Dynamic Multimedia Annotation Tool.

Automated Benchmarking in Content-based Image Retrieval. The Reality of Content-based Image Retrieval. In Proceeding of the meeting Suchbilder, Berlin, Germany. Second generation benchmarking and application oriented evaluation. Towards a fair benchmark for image browsers. A communication protocol for content-based multimedia retrieval.

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Lernen von Merkmalsgewichtungen beim inhaltsbasierten Suchen in grossenBilddatenbanken Content-based image retrieval. Learning features weights from user behavior in Content-Based ImageRetrieval. Strategies for positive and negative relevance feedback in imageretrieval. Efficient access methods for content-based image retrieval with invertedfiles. Relevance feedback and term weighting schemes for content-based imageretrieval.

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Content-based query of image databases, inspirations from text retrieval: In Informatiktage 99, Bad Schussenried, Germany. Learning a similarity-based distance measure for image database organizationfrom human partitionings of an image set.

  1. Exploratory image databases : content-based retrieval, Simone Santini, (electronic resource)?
  2. Exploratory Image Databases : Simone Santini : ?
  3. The Bride And The Homeless.
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Using human partitionings of image sets to learn a similarity-baseddistance measure for the organization of image databases. Archival and retrieval for large image databases: Archival and retrieval of historical watermark images.

Archivage et recherche d'images de filigranes. National sur l'Ecrit et le Document, Nantes, France.

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Strategies for positive and negative relevance feedback in image retrieval No. Serendipitous Exploration of Large-scale Product Catalogs. A new approach to image databases, the work is divided into four central parts: Christmas posting dates Learn more. Joint estimation and lightspeed comparison of mixture models. With the recent advances in wireless communication technology and availability of multimedia capable phones it has become vital to enable query operation in image databases and retrieve results based on the image content. Check out the top books of the year on our page Best Books of

Exchange-Based Diffusion in Hb-Graphs: Dual diffusion model of spreading activation for content-based image retrieval No. Steps towards version 2 No. The success and the future of visual information retrieval depends on the cutting edge research and applications explored in this book. It combines the expertise from both computer vision and database research. How do you use "data mining" to search for an image if you do not have "key words" to search? Exploratory Image Databases introduces the idea that it is possible to solve this problem by merging database systems into a single search and browse activity called "exploration.

A new approach to image databases, the work is divided into four central parts: Imagine the difficulty of building and using a database for "face recognition," where an image of a face is used. In order to effectively use the image a huge number of characteristics would need to be entered in the database. The goal of future image databases is to use hardware and software to recognize and categorize images without typing in characteristics. The Best Books of Check out the top books of the year on our page Best Books of Product details Format Hardback pages Dimensions x x