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» Learning Mid-Level Features For Recognition
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GECCO
2006
Springer
169views Optimization» more  GECCO 2006»
13 years 11 months ago
An open-set speaker identification system using genetic learning classifier system
This paper presents the design and implementation of an adaptive open-set speaker identification system with genetic learning classifier systems. One of the challenging problems i...
WonKyung Park, Jae C. Oh, Misty K. Blowers, Matt B...
CVPR
2009
IEEE
1084views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Describing Objects by their Attributes
We propose to shift the goal of recognition from naming to describing. Doing so allows us not only to name familiar objects, but also: to report unusual aspects of a familiar ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...
JMM2
2008
92views more  JMM2 2008»
13 years 7 months ago
Dimensionality Reduction using SOM based Technique for Face Recognition
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms name...
Dinesh Kumar, C. S. Rai, Shakti Kumar
ICCV
2011
IEEE
12 years 7 months ago
Scene Recognition and Weakly Supervised Object Localization with Deformable Part-Based Models
Weakly supervised discovery of common visual structure in highly variable, cluttered images is a key problem in recognition. We address this problem using deformable part-based mo...
Megha Pandey, Svetlana Lazebnik
CVPR
2007
IEEE
14 years 9 months ago
Semantic Hierarchies for Visual Object Recognition
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior kno...
Marcin Marszalek, Cordelia Schmid