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» Adapting RBF Neural Networks to Multi-Instance Learning
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ICASSP
2011
IEEE
12 years 8 months ago
Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence
— In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SIM...
Hao Chen, Yu Gong, Xia Hong
ISCIS
2005
Springer
13 years 10 months ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
HIS
2008
13 years 6 months ago
A Sequential Learning Resource Allocation Network for Image Processing Applications
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
Stefan Wildermann, Jürgen Teich
MVA
2000
172views Computer Vision» more  MVA 2000»
13 years 6 months ago
Partial Face Extraction and Recognition Using Radial Basis Function Networks
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
Nan He, Kiminori Sato, Yukitoshi Takahashi