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https://www.um.edu.mt/library/oar/handle/123456789/26333| Title: | Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation |
| Authors: | Schutte, Klamer Bouma, Henri Schavemaker, John Daniele, Laura Sappelli, Maya Koot, Gijs Endebak, Pieter Azzopardi, George Spitters, Martijn Boer, Maaike de Kruithof, Maarten Brandt, Paul |
| Keywords: | Image processing Content-based image retrieval Concept learning |
| Issue Date: | 2015-06 |
| Publisher: | Institute of Electrical and Electronics Engineers Inc. |
| Citation: | Schutte, K., Bouma, H., Schavemaker, J., Daniele, L., Sappelli, M., Koot, G.,...Brandt, P. (2015). Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation. In 13th International Workshop on Content-Based Multimedia Indexing (CBMI), Prague, Czech Republic. 1-4. |
| Abstract: | The number of networked cameras is growing exponentially. Multiple applications in different domains result in an increasing need to search semantically over video sensor data. In this paper, we present the GOOSE demonstrator, which is a real-time general-purpose search engine that allows users to pose natural language queries to retrieve corresponding images. Top-down, this demonstrator interprets queries, which are presented as an intuitive graph to collect user feedback. Bottomup, the system automatically recognizes and localizes concepts in images and it can incrementally learn novel concepts. A smart ranking combines both and allows effective retrieval of relevant images. |
| Description: | This research was performed in the GOOSE project, which is jointly funded by the MIST research program of the Dutch Ministry of Defense and the AMSN enabling technology program. |
| URI: | https://www.um.edu.mt/library/oar//handle/123456789/26333 |
| Appears in Collections: | Scholarly Works - FacICTAI |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ConferencePaper_Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation.pdf | 461.83 kB | Adobe PDF | View/Open |
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