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» Small codes and large image databases for recognition
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TEC
2002
81views more  TEC 2002»
14 years 11 months ago
Genetic object recognition using combinations of views
We investigate the application of genetic algorithms (GAs) for recognizing real two-dimensional (2-D) or three-dimensional (3-D) objects from 2-D intensity images, assuming that th...
George Bebis, Evangelos A. Yfantis, Sushil J. Loui...
ICCV
2011
IEEE
13 years 12 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
STOC
2007
ACM
179views Algorithms» more  STOC 2007»
16 years 3 days ago
Towards 3-query locally decodable codes of subexponential length
A q-query Locally Decodable Code (LDC) encodes an n-bit message x as an N-bit codeword C(x), such that one can probabilistically recover any bit xi of the message by querying only...
Sergey Yekhanin
ICANN
2005
Springer
15 years 5 months ago
Handwritten Digit Recognition with Nonlinear Fisher Discriminant Analysis
Abstract. To generalize the Fisher Discriminant Analysis (FDA) algorithm to the case of discriminant functions belonging to a nonlinear, finite dimensional function space F (Nonli...
Pietro Berkes
ECCV
2010
Springer
15 years 4 months ago
Semantic Label Sharing for Learning with Many Categories
In an object recognition scenario with tens of thousands of categories, even a small number of labels per category leads to a very large number of total labels required. We propose...