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ICMCS
2000
IEEE
116views Multimedia» more  ICMCS 2000»
13 years 11 months ago
Non-linear Relevance Feedback: Improving the Performance of Content-Based Retrieval Systems
In this paper, a non-linear relevance feedback mechanism is proposed for increasing the performance and the reliability of content-based retrieval systems. In particular, the huma...
Nikolaos D. Doulamis, Anastasios D. Doulamis, Stef...
ICTIR
2009
Springer
14 years 1 months ago
A Four-Factor User Interaction Model for Content-Based Image Retrieval
In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques i...
Haiming Liu 0002, Victoria S. Uren, Dawei Song, St...
CISST
2004
164views Hardware» more  CISST 2004»
13 years 8 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp
ICIP
1997
IEEE
14 years 8 months ago
Content-Based Image Retrieval with Relevance Feedback in MARS
Yong Rui, Thomas S. Huang, Sharad Mehrotra
MLDM
2001
Springer
13 years 11 months ago
Adaptive Query Shifting for Content-Based Image Retrieval
: Despite the efforts to reduce the semantic gap between user perception of similarity and featurebased representation of images, user interaction is essential to improve retrieval...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera