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» A comparative study of two object recognition methods
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CVPR
2011
IEEE
14 years 12 months ago
Boundary Preserving Dense Local Regions
We propose a dense local region detector to extract features suitable for image matching and object recognition tasks. Whereas traditional local interest operators rely on repeata...
Jaechul Kim, Kristen Grauman
EDBT
2008
ACM
167views Database» more  EDBT 2008»
16 years 4 months ago
HISSCLU: a hierarchical density-based method for semi-supervised clustering
In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
Christian Böhm, Claudia Plant
WWW
2009
ACM
15 years 8 months ago
Extracting data records from the web using tag path clustering
Fully automatic methods that extract lists of objects from the Web have been studied extensively. Record extraction, the first step of this object extraction process, identifies...
Gengxin Miao, Jun'ichi Tatemura, Wang-Pin Hsiung, ...
147
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ICASSP
2011
IEEE
14 years 7 months ago
Relevance language modeling for speech recognition
Language models for speech recognition tend to be brittle across domains, since their performance is vulnerable to changes in the genre or topic of the text on which they are trai...
Kuan-Yu Chen, Berlin Chen
ICCV
2005
IEEE
16 years 5 months ago
Creating Efficient Codebooks for Visual Recognition
Visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and...
Bill Triggs, Frédéric Jurie