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ORCID6th MDM/KDD 2005: Chicago, Illinois, USA
- Fatma Bouali, Latifur Khan, Florent Masseglia:
Proceedings of the 6th international workshop on Multimedia data mining - mining integrated media and complex data, MDM 2005, Chicago, Illinois, USA, August 21, 2005. ACM 2005 - Anne-Muriel Arigon, Anne Tchounikine, Maryvonne Miquel:
A multiversion model for multimedia data warehouse. 7-13 - Pierre Gançarski, Cédric Wemmert:
Collaborative multi-strategy classification: application to per-pixel analysis of images. 15-22 - Ruoming Jin, Kaushik Sinha, Gagan Agrawal:
A framework to support multiple query optimization for complex mining tasks. 23-32 - Maude Manouvrier, Marta Rukoz, Geneviève Jomier:
A generalized metric distance between hierarchically partitioned images. 33-41 - Rokia Missaoui, Roman M. Palenichka:
Effective image and video mining: an overview of model-based approaches. 43-52 - Valery A. Petrushin, Gang Wei, Rayid Ghani, Anatole Gershman:
Multiple sensor integration for indoor surveillance. 53-60 - Vincent S. Tseng, Chon-Jei Lee, Ja-Hwung Su:
Classify By Representative Or Associations (CBROA): a hybrid approach for image classification. 61-69 - Chengcui Zhang, Xin Chen:
OCRS: an Interactive Object-based Image Clustering and Retrieval System. 71-78 - Gal Lavee, Latifur Khan
, Bhavani Thuraisingham:
A framework for a video analysis tool for suspicious event detection. 79-84 - Ryan Layfield, Latifur Khan, Bhavani Thuraisingham:
Message correlation in automated communication surveillance through singular value decomposition and word frequency association. 85-88 - Chuanjun Li, B. Prabhakaran:
A similarity measure for motion stream segmentation and recognition. 89-94 - Sylvain Mongy, Fatma Bouali, Chabane Djeraba:
Analyzing user's behavior on a video database. 95-100 - Shawn D. Newsam:
Seeing and reading red: hue and color-word correlation in images and attendant text on the WWW. 101-106 - Aparna S. Varde, Elke A. Rundensteiner, Carolina Ruiz, Mohammed Maniruzzaman, Richard D. Sisson Jr.:
Learning semantics-preserving distance metrics for clustering graphical data. 107-112
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