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MLDM
1999
Springer
14 years 2 months ago
Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Irwin King, Tak-Kan Lau
MM
2009
ACM
209views Multimedia» more  MM 2009»
14 years 4 months ago
Brain state decoding for rapid image retrieval
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...
MIR
2005
ACM
137views Multimedia» more  MIR 2005»
14 years 3 months ago
A content-based image retrieval system for fish taxonomy
It is estimated that less than ten percent of the world’s species have been discovered and described. The main reason for the slow pace of new species description is that the sc...
Yixin Chen, Henry L. Bart Jr., Fei Teng
CVPR
2008
IEEE
15 years 2 days ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
ICDE
1994
IEEE
135views Database» more  ICDE 1994»
14 years 2 months ago
QBISM: Extending a DBMS to Support 3D Medical Images
We describe the design and implementation of QBISM (Query By Interactive, Spatial Multimedia), a prototype for querying and visualizing 3D spatial data. Our first application is i...
Manish Arya, William F. Cody, Christos Faloutsos, ...