Semisupervised biased maximum margin analysis for interactive image retrieval
With many potential practical applications, content-based image retrieval (CBIR) has attracted substantial attention during the past few years. A variety of relevance feedback (RF) schemes have been developed as a powerful tool to bridge the semantic gap between low-level visual features and high-le...
Main Authors: | Zhang, Lining., Wang, Lipo., Lin, Weisi. |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2012
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/94522 http://hdl.handle.net/10220/8191 |
Similar Items
-
Generalized biased discriminant analysis for content-based image retrieval
by: Zhang, Lining., et al.
Published: (2012) -
Multi-associative neural networks and their applications to learning and retrieving complex spatio-temporal sequences
by: Wang, Lipo.
Published: (2012) -
Text-based image retrieval using image captioning
by: Tan, Kah Hwa
Published: (2019) -
Interactive E-learning environment for maximum power transfer in RFIC
by: Ratna
Published: (2019) -
On the classical limit of phasespace formulation of quantum mechanics : entropy
by: Wang, Lipo.
Published: (2012)