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» Semantic based image retrieval: a probabilistic approach
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NIPS
2001
14 years 11 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
SIGIR
2010
ACM
14 years 10 months ago
Visual summarization of web pages
Visual summarization is an attractive new scheme to summarize web pages, which can help achieve a more friendly user experience in search and re-finding tasks by allowing users qu...
Binxing Jiao, Linjun Yang, Jizheng Xu, Feng Wu
SIGMOD
2007
ACM
192views Database» more  SIGMOD 2007»
15 years 10 months ago
Benchmarking declarative approximate selection predicates
Declarative data quality has been an active research topic. The fundamental principle behind a declarative approach to data quality is the use of declarative statements to realize...
Amit Chandel, Oktie Hassanzadeh, Nick Koudas, Moha...
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
15 years 10 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler

Publication
1763views
15 years 6 months ago
Reranking with Contextual dissimilarity measures from representational Bregman k-means
We present a novel reranking framework for Content Based Image Retrieval (CBIR) systems based on con-textual dissimilarity measures. Our work revisit and extend the method of Perro...
Olivier Schwander, Frank Nielsen