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CLEF
2010
Springer
13 years 8 months ago
Blind Relevance Feedback for the ImageCLEF Wikipedia Retrieval Task
In this paper we will describe Berkeley's approach to the ImageCLEF Wikipedia Retrieval task for 2010. Our approach to this task was primarily to use text-based searches on th...
Ray R. Larson
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
JMLR
2010
127views more  JMLR 2010»
13 years 2 months ago
Content-based Image Retrieval with Multinomial Relevance Feedback
The paper considers an interactive search paradigm in which at each round a user is presented with a set of k images and is required to select one that is closest to her target. P...
Dorota Glowacka, John Shawe-Taylor
ECIR
2010
Springer
13 years 9 months ago
On Improving Pseudo-Relevance Feedback Using Pseudo-Irrelevant Documents
Abstract. Pseudo-Relevance Feedback (PRF) assumes that the topranking n documents of the initial retrieval are relevant and extracts expansion terms from them. In this work, we int...
Karthik Raman, Raghavendra Udupa, Pushpak Bhattach...
ICMCS
2006
IEEE
124views Multimedia» more  ICMCS 2006»
14 years 1 months ago
Content-Free Image Retrieval using Bayesian Product Rule
Content-free image retrieval uses accumulated user feedback records to retrieve images without analyzing image pixels. We present a Bayesian-based algorithm to analyze user feedba...
David Liu, Tsuhan Chen