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» Approximate algorithms for neural-Bayesian approaches
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ICPR
2000
IEEE
15 years 2 months ago
Modeling Range Images with Bounded Error Triangular Meshes without Optimization
This paper presents a new technique for approximating range images by means of adaptive triangular meshes with a bounded approximation error and without applying optimization. Thi...
Angel Domingo Sappa, Miguel Angel García
SBCCI
2003
ACM
129views VLSI» more  SBCCI 2003»
15 years 3 months ago
Hyperspectral Images Clustering on Reconfigurable Hardware Using the K-Means Algorithm
Unsupervised clustering is a powerful technique for understanding multispectral and hyperspectral images, being k-means one of the most used iterative approaches. It is a simple th...
Abel Guilhermino S. Filho, Alejandro César ...
IR
2010
14 years 8 months ago
A general approximation framework for direct optimization of information retrieval measures
Recently direct optimization of information retrieval (IR) measures becomes a new trend in learning to rank. Several methods have been proposed and the effectiveness of them has ...
Tao Qin, Tie-Yan Liu, Hang Li
ECCV
2004
Springer
15 years 11 months ago
A Robust Algorithm for Characterizing Anisotropic Local Structures
This paper proposes a robust estimation and validation framework for characterizing local structures in a positive multi-variate continuous function approximated by a Gaussian-base...
Kazunori Okada, Dorin Comaniciu, Navneet Dalal, Ar...
NETWORKING
2000
14 years 11 months ago
Computing Blocking Probabilities in Multi-class Wavelength Routing Networks
We present an approximate analytical method to compute efficiently the call blocking probabilities in wavelength routing networks with multiple classes of calls. The model is fairl...
Sridhar Ramesh, George N. Rouskas, Harry G. Perros