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Principles of visual information retrievalJanuary 2000
Publisher:
  • Springer-Verlag
  • Berlin, Heidelberg
ISBN:978-1-85233-381-2
Published:01 January 2000
Pages:
340
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Bibliometrics
Abstract

No abstract available.

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chapter
Color-based retrieval
pp 11–49
chapter
Feature similarity
pp 121–143
chapter
Feature selection and visual learning
pp 145–162
chapter
chapter
Trademark image retrieval
pp 319–350

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  1. Rotter P (2014). Relevance feedback based on n-tuplewise comparison and the ELECTRE methodology and an application in content-based image retrieval, Multimedia Tools and Applications, 72:1, (667-685), Online publication date: 1-Sep-2014.
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  3. Choroś K Reduction of faulty detected shot cuts and cross dissolve effects in video segmentation process of different categories of digital videos Transactions on computational collective intelligence V, (124-139)
  4. Yao A, Wang G, Lin X and Chai X (2010). An incremental Bhattacharyya dissimilarity measure for particle filtering, Pattern Recognition, 43:4, (1244-1256), Online publication date: 1-Apr-2010.
  5. Pires G and Araújo A A stochastic neural model for fast classification of binary images Proceedings of the 2009 international joint conference on Neural Networks, (2212-2217)
  6. Torres R, Falcão A, Gonçalves M, Papa J, Zhang B, Fan W and Fox E (2009). A genetic programming framework for content-based image retrieval, Pattern Recognition, 42:2, (283-292), Online publication date: 1-Feb-2009.
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    Luo H, Gao Y, Xue X, Peng J and Fan J (2008). Incorporating feature hierarchy and boosting to achieve more effective classifier training and concept-oriented video summarization and skimming, ACM Transactions on Multimedia Computing, Communications, and Applications, 4:1, (1-25), Online publication date: 1-Jan-2008.
  8. Choroś K and Gonet M Effectiveness of Video Segmentation Techniques for Different Categories of Videos Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems, (34-45)
  9. Snoek C and Worring M (2009). Concept-Based Video Retrieval, Foundations and Trends in Information Retrieval, 2:4, (215-322), Online publication date: 1-Apr-2008.
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    Oerlemans A, Rijsdam J and Lew M Real-time object tracking with relevance feedback Proceedings of the 6th ACM international conference on Image and video retrieval, (101-104)
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    Arifin S and Cheung P A computation method for video segmentation utilizing the pleasure-arousal-dominance emotional information Proceedings of the 15th ACM international conference on Multimedia, (68-77)
  12. Choraś R CBIR based on color and low-level texture features Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, (259-263)
  13. Lew M Visual information retrieval Proceedings of the 9th international conference on Advances in visual information systems, (1-4)
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  15. Georgakis A and Li H Content based image retrieval using a bootstrapped SOM network Proceedings of the Third international conference on Advnaces in Neural Networks - Volume Part II, (595-601)
  16. Qamra A, Meng Y and Chang E (2005). Enhanced Perceptual Distance Functions and Indexing for Image Replica Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27:3, (379-391), Online publication date: 1-Mar-2005.
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    Ferecatu M, Boujemaa N and Crucianu M Hybrid visual and conceptual image representation within active relevance feedback context Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval, (209-216)
  18. Starostenko O, Chávez-Aragón A, Sánchez J and Ostróvskaya Y A hybrid approach for image retrieval with ontological content-based indexing Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications, (997-1004)
  19. Bensefia A, Paquet T and Heutte L (2005). A writer identification and verification system, Pattern Recognition Letters, 26:13, (2080-2092), Online publication date: 1-Oct-2005.
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  22. Change Detection in Aerial Images Proceedings of the 1st Canadian Conference on Computer and Robot Vision, (354-360)
  23. Laaksonen J, Koskela J and Oja E (2004). Class distribution on SOM surfaces for feature extraction and object retrieval, Neural Networks, 17:8-9, (1121-1133), Online publication date: 1-Oct-2004.
  24. Image Retrieval by Ontological Description of Shapes (IRONS), Early Results Proceedings of the 1st Canadian Conference on Computer and Robot Vision, (341-346)
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    Fan J, Luo H and Lin X Semantic video classification by integrating flexible mixture model with adaptive EM algorithm Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval, (9-16)
  26. Stejić Z, Takama Y and Hirota K (2003). Genetic algorithm-based relevance feedback for image retrieval using local similarity patterns, Information Processing and Management: an International Journal, 39:1, (1-23), Online publication date: 1-Jan-2003.
  27. Brandt S, Laaksonen J and Oja E (2019). Statistical Shape Features for Content-Based Image Retrieval, Journal of Mathematical Imaging and Vision, 17:2, (187-198), Online publication date: 1-Sep-2002.
Contributors
  • Leiden University

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