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» The Localization Hypothesis and Machines
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ICRA
2006
IEEE
123views Robotics» more  ICRA 2006»
14 years 4 months ago
Simultaneous Localization and Mapping with Environmental Structure Prediction
—Traditionally, simultaneous localization and mapping (SLAM) algorithms solve the localization and mapping problem in explored regions. This paper presents a prediction-based SLA...
H. Jacky Chang, C. S. George Lee, Yung-Hsiang Lu, ...
ECCV
2010
Springer
14 years 1 months ago
Recursive Coarse-to-Fine Localization for fast Object Detection
Cascading techniques are commonly used to speed-up the scan of an image for object detection. However, cascades of detectors are slow to train due to the high number of detectors a...
Marco Pedersoli, Jordi Gonzàlez, Andrew D. Bagdan...
IJRR
2010
185views more  IJRR 2010»
13 years 8 months ago
FISST-SLAM: Finite Set Statistical Approach to Simultaneous Localization and Mapping
The solution to the problem of mapping an environment and at the same time using this map to localize (the simultaneous localization and mapping, SLAM, problem) is a key prerequis...
Bharath Kalyan, K. W. Lee, W. Sardha Wijesoma
ICML
2006
IEEE
14 years 10 months ago
Totally corrective boosting algorithms that maximize the margin
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...
Gunnar Rätsch, Jun Liao, Manfred K. Warmuth
ICML
2004
IEEE
14 years 10 months ago
Learning first-order rules from data with multiple parts: applications on mining chemical compound data
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
Cholwich Nattee, Sukree Sinthupinyo, Masayuki Numa...