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» Extracting general-purpose features from LIDAR data
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ICML
2010
IEEE
15 years 3 months ago
Learning Fast Approximations of Sparse Coding
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Karol Gregor, Yann LeCun
ICCV
2011
IEEE
14 years 2 months ago
What Characterizes a Shadow Boundary under the Sun and Sky?
Despite decades of study, robust shadow detection remains difficult, especially within a single color image. We describe a new approach to detect shadow boundaries in images of o...
Xiang Huang, Gang Hua, Jack Tumblin, Lance William...
EMMCVPR
2007
Springer
15 years 8 months ago
3D Computation of Gray Level Co-occurrence in Hyperspectral Image Cubes
This study extended the computation of GLCM (gray level co-occurrence matrix) to a three-dimensional form. The objective was to treat hyperspectral image cubes as volumetric data s...
Fuan Tsai, Chun-Kai Chang, Jian-Yeo Rau, Tang-Huan...
HAPTICS
2006
IEEE
15 years 8 months ago
Haptic-Based Biometrics: A Feasibility Study
Biometric systems identify users based on behavioral or physiological characteristics. The advantages of such systems over traditional authentication methods such as passwords are...
Mauricio Orozco Trujillo, Yednek Asfaw, Shervin Sh...
NIPS
2001
15 years 3 months ago
On the Generalization Ability of On-Line Learning Algorithms
In this paper, it is shown how to extract a hypothesis with small risk from the ensemble of hypotheses generated by an arbitrary on-line learning algorithm run on an independent an...
Nicolò Cesa-Bianchi, Alex Conconi, Claudio ...