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» Evaluating Feature Selection for SVMs in High Dimensions
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90
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ICCV
2009
IEEE
16 years 5 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
107
Voted
CIKM
2000
Springer
15 years 4 months ago
Vector Approximation based Indexing for Non-uniform High Dimensional Data Sets
With the proliferation of multimedia data, there is increasing need to support the indexing and searching of high dimensional data. Recently, a vector approximation based techniqu...
Hakan Ferhatosmanoglu, Ertem Tuncel, Divyakant Agr...
121
Voted
TVCG
2011
152views more  TVCG 2011»
14 years 7 months ago
Automated Analytical Methods to Support Visual Exploration of High-Dimensional Data
—Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the numbe...
Andrada Tatu, Georgia Albuquerque, Martin Eisemann...
164
Voted
MM
2010
ACM
462views Multimedia» more  MM 2010»
15 years 19 days ago
KPB-SIFT: a compact local feature descriptor
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...
Gangqiang Zhao, Ling Chen, Gencai Chen, Junsong Yu...
195
Voted
PLDI
2009
ACM
16 years 1 months ago
Chameleon: adaptive selection of collections
Languages such as Java and C#, as well as scripting languages like Python, and Ruby, make extensive use of Collection classes. A collection implementation represents a fixed choic...
Ohad Shacham, Martin T. Vechev, Eran Yahav