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» Semantic kernel learning for interactive image retrieval
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ICIP
2000
IEEE
14 years 9 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
ICMCS
2005
IEEE
184views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Fuzzy relevance feedback in content-based image retrieval systems using radial basis function network
This paper presents a new framework called fuzzy relevance feedback in interactive content-based image retrieval (CBIR) systems based on soft-decision. An efficient learning appro...
Kim-Hui Yap, Kui Wu
WSDM
2010
ACM
215views Data Mining» more  WSDM 2010»
14 years 5 months ago
GeoFolk: Latent spatial semantics in Web 2.0 social media
We describe an approach for multi-modal characterization of social media by combining text features (e.g. tags as a prominent example of short, unstructured text labels) with spat...
Sergej Sizov
ICIP
1998
IEEE
14 years 9 months ago
Semantic Visual Templates: Linking Visual Features to Semantics
The rapid growth of visual data over the last few years has lead to many schemes for retrieving such data. With content-based systems today, there exists a significant gap between...
Shih-Fu Chang, William Chen, Hari Sundaram
MM
2005
ACM
209views Multimedia» more  MM 2005»
14 years 1 months ago
Learning an image-word embedding for image auto-annotation on the nonlinear latent space
Latent Semantic Analysis (LSA) has shown encouraging performance for the problem of unsupervised image automatic annotation. LSA conducts annotation by keywords propagation on a l...
Wei Liu, Xiaoou Tang