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» Learning Visual Invariance
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IJCV
2008
192views more  IJCV 2008»
13 years 10 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
NDSS
2008
IEEE
14 years 4 months ago
Limits of Learning-based Signature Generation with Adversaries
Automatic signature generation is necessary because there may often be little time between the discovery of a vulnerability, and exploits developed to target the vulnerability. Mu...
Shobha Venkataraman, Avrim Blum, Dawn Song
EPIA
2009
Springer
14 years 4 months ago
Learning Visual Object Categories with Global Descriptors and Local Features
Different types of visual object categories can be found in real-world applications. Some categories are very heterogeneous in terms of local features (broad categories) while oth...
Rui Pereira, Luís Seabra Lopes
CVPR
2011
IEEE
13 years 6 months ago
Learning the Easy Things First: Self-Paced Visual Category Discovery
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
Yong Jae Lee, Kristen Grauman
ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
14 years 4 months ago
Model-based and model-free reinforcement learning for visual servoing
— To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by b...
Amir Massoud Farahmand, Azad Shademan, Martin J&au...