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146
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RSS
2007
152views Robotics» more  RSS 2007»
15 years 4 months ago
Dimensionality Reduction Using Automatic Supervision for Vision-Based Terrain Learning
Abstract— This paper considers the problem of learning to recognize different terrains from color imagery in a fully automatic fashion, using the robot’s mechanical sensors as ...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
ICFEM
2009
Springer
15 years 9 months ago
Role-Based Symmetry Reduction of Fault-Tolerant Distributed Protocols with Language Support
Fault-tolerant (FT) distributed protocols (such as group membership, consensus, etc.) represent fundamental building blocks for many practical systems, e.g., the Google File System...
Péter Bokor, Marco Serafini, Neeraj Suri, H...
CVPR
2007
IEEE
15 years 9 months ago
A Graph Reduction Method for 2D Snake Problems
Energy-minimizing active contour models (snakes) have been proposed for solving many computer vision problems such as object segmentation, surface reconstruction, and object track...
Jianhua Yan, Keqi Zhang, Chengcui Zhang, Shu-Ching...
151
Voted
SAC
2006
ACM
15 years 8 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
116
Voted
ECCV
2004
Springer
16 years 4 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Marco Loog, Bram van Ginneken, Robert P. W. Duin