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» Comparing image-based localization methods
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SAB
2010
Springer
117views Optimization» more  SAB 2010»
13 years 7 months ago
Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
Sebastian Risi, Kenneth O. Stanley
ICCV
2003
IEEE
14 years 11 months ago
Learning a Locality Preserving Subspace for Visual Recognition
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...
Xiaofei He, Shuicheng Yan, Yuxiao Hu, HongJiang Zh...
ICRA
2009
IEEE
117views Robotics» more  ICRA 2009»
14 years 3 months ago
Modeling RFID signal strength and tag detection for localization and mapping
— In recent years, there has been an increasing interest within the robotics community in investigating whether Radio Frequency Identification (RFID) technology can be utilized ...
Dominik Joho, Christian Plagemann, Wolfram Burgard
ICRA
2008
IEEE
142views Robotics» more  ICRA 2008»
14 years 3 months ago
Gaussian mixture models for probabilistic localization
— One of the key tasks during the realization of probabilistic approaches to localization is the design of a proper sensor model, that calculates the likelihood of a measurement ...
Patrick Pfaff, Christian Plagemann, Wolfram Burgar...
ICIP
2007
IEEE
14 years 3 months ago
Locally Competitive Algorithms for Sparse Approximation
Practical sparse approximation algorithms (particularly greedy algorithms) suffer two significant drawbacks: they are difficult to implement in hardware, and they are inefficie...
Christopher J. Rozell, Don H. Johnson, Richard G. ...