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ICMCS
2000
IEEE
116views Multimedia» more  ICMCS 2000»
13 years 12 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...
ICIP
2010
IEEE
13 years 5 months ago
Image retrieval with feature selection and relevance feedback
This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from...
Yu Sun, Bir Bhanu
ISCIS
2009
Springer
14 years 2 months ago
Dynamic feature weights with relevance feedback in content-based image retrieval
— In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights. The proposed method utilizes intracluste...
Esin Guldogan, Moncef Gabbouj
ICMCS
1999
IEEE
181views Multimedia» more  ICMCS 1999»
13 years 11 months ago
Interactive Content-Based Retrieval in Video Databases Using Fuzzy Classification and Relevance Feedback
This paper presents an integrated framework for interactive content-based retrieval in video databases by means of visual queries. The proposed system incorporates algorithms for ...
Anastasios D. Doulamis, Yannis S. Avrithis, Nikola...
CISST
2004
164views Hardware» more  CISST 2004»
13 years 9 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