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» Optimizing Learning in Image Retrieval
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VLDB
2000
ACM
121views Database» more  VLDB 2000»
13 years 11 months ago
Optimizing Multi-Feature Queries for Image Databases
In digital libraries image retrieval queries can be based on the similarity of objects, using several feature attributes like shape, texture, color or text. Such multi-feature que...
Ulrich Güntzer, Wolf-Tilo Balke, Werner Kie&s...
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
CVPR
2000
IEEE
14 years 9 months ago
Discriminant-EM Algorithm with Application to Image Retrieval
In Proc. of IEEE Conf. on CVPR'2000, Vol.I, pp.222-227, Hilton Head Island, SC, 2000 In many vision applications, the practice of supervised learning faces several difficulti...
Ying Wu, Qi Tian, Thomas S. Huang
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
14 years 2 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
AMR
2007
Springer
140views Multimedia» more  AMR 2007»
14 years 1 months ago
Learning Distance Functions for Automatic Annotation of Images
This paper gives an overview of recent approaches towards image representation and image similarity computation for content-based image retrieval and automatic image annotation (ca...
Josip Krapac, Frédéric Jurie