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» Textural Features and Relevance Feedback for Image Retrieval
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ISBI
2011
IEEE
14 years 3 months ago
Group sparsity based classification for cervigram segmentation
This paper presents an algorithm to classify pixels in uterine cervix images into two classes, namely normal and abnormal tissues, and simultaneously select relevant features, usi...
Yang Yu, Junzhou Huang, Shaoting Zhang, Christophe...
CVPR
2011
IEEE
14 years 3 months ago
Total Recall II: Query Expansion Revisited
Most effective particular object and image retrieval approaches are based on the bag-of-words (BoW) model. All state-of-the-art retrieval results have been achieved by methods tha...
Ondrej Chum, Andrej Mikulik, Michal Perdoch, Jiri ...
SIGIR
1998
ACM
14 years 11 months ago
Exploring the Similarity Space
Ranked queries are used to locate relevant documents in text databases. In a ranked query a list of terms is specified, then the documents that most closely match the query are re...
Justin Zobel, Alistair Moffat
CIVR
2008
Springer
166views Image Analysis» more  CIVR 2008»
15 years 1 months ago
A probabilistic ranking framework using unobservable binary events for video search
Recent content-based video retrieval systems combine output of concept detectors (also known as high-level features) with text obtained through automatic speech recognition. This ...
Robin Aly, Djoerd Hiemstra, Arjen P. de Vries, Fra...
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 7 days ago
Catching the drift: learning broad matches from clickthrough data
Identifying similar keywords, known as broad matches, is an important task in online advertising that has become a standard feature on all major keyword advertising platforms. Eff...
Sonal Gupta, Mikhail Bilenko, Matthew Richardson