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» Learning Bayesian Networks from Incomplete Databases
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ESANN
2001
14 years 16 days ago
Coding the outputs of multilayer feedforward
In this paper, we present an empirical comparison among four different schemes of coding the outputs of a Multilayer Feedforward networks. Results are obtained for eight different ...
Mercedes Fernández-Redondo, Carlos Hern&aac...
ICPR
2002
IEEE
15 years 7 days ago
Graph of Neural Networks for Pattern Recognition
This paper presents a new architecture of neural networks designed for pattern recognition. The concept of induction graphs coupled with a divide-and-conquer strategy defines a Gr...
Hubert Cardot, Olivier Lezoray
CVPR
2012
IEEE
12 years 1 months ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
ECCV
2000
Springer
15 years 1 months ago
Learning to Recognize 3D Objects with SNoW
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 11 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...