Adaptive Multimedia Retrieval: User, Context, and Feedback 4th International Workshop, AMR 2006, Geneva, Switzerland, July 27-28, 2006, Revised Selected Papers /
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , , , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2007.
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Σειρά: | Lecture Notes in Computer Science,
4398 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Ontology-Based Retrieval and Annotation
- A Method for Processing the Natural Language Query in Ontology-Based Image Retrieval System
- SAFIRE: Towards Standardized Semantic Rich Image Annotation
- Ontology-Supported Video Modeling and Retrieval
- Ranking and Similarity Measurements
- Learning to Retrieve Images from Text Queries with a Discriminative Model
- A General Principled Method for Image Similarity Validation
- Rank-Test Similarity Measure Between Video Segments for Local Descriptors
- Music Information Retrieval
- Can Humans Benefit from Music Information Retrieval?
- Visual Modelling
- A New Approach to Probabilistic Image Modeling with Multidimensional Hidden Markov Models
- 3D Face Recognition by Modeling the Arrangement of Concave and Convex Regions
- Fuzzy Semantic Action and Color Characterization of Animation Movies in the Video Indexing Task Context
- Retrieval of Document Images Based on Page Layout Similarity
- Adaptive Retrieval
- Multimedia Content Adaptation Within the CAIN Framework Via Constraints Satisfaction and Optimization
- Aspects of Adaptivity in P2P Information Retrieval
- Interactive Museum Guide: Accurate Retrieval of Object Descriptions
- Structuring Multimedia
- Semantic Image Retrieval Using Region-Based Relevance Feedback
- Image Retrieval with Segmentation-Based Query
- Fast Structuring of Large Television Streams Using Program Guides
- User Integration and Profiling
- Variation of Relevance Assessments for Medical Image Retrieval
- An Efficient Collaborative Information Retrieval System by Incorporating the User Profile
- The Potential of User Feedback Through the Iterative Refining of Queries in an Image Retrieval System.