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» Training Methods for Adaptive Boosting of Neural Networks
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IJISTA
2010
100views more  IJISTA 2010»
14 years 8 months ago
Development of an awakening detection system with the NN and adaptation for fluctuation of brightness quantity in the captured i
Recently, accidents such that seniors fall down from the bed in care facilities or hospitals are increased. To prevent these accidents, we have developed an awakening detection sys...
Nobuhisa Yamanaka, Hironobu Satoh, Fumiaki Takeda
RAID
2009
Springer
15 years 4 months ago
Adaptive Anomaly Detection via Self-calibration and Dynamic Updating
The deployment and use of Anomaly Detection (AD) sensors often requires the intervention of a human expert to manually calibrate and optimize their performance. Depending on the si...
Gabriela F. Cretu-Ciocarlie, Angelos Stavrou, Mich...
IJCNN
2008
IEEE
15 years 4 months ago
On-line bagging Negative Correlation Learning
— Negative Correlation Learning (NCL) has been showing to outperform other ensemble learning approaches in off-line mode. A key point to the success of NCL is that the learning o...
Fernanda L. Minku, Xin Yao
IDA
1998
Springer
14 years 9 months ago
Self-Organized-Expert Modular Network for Classification of Spatiotemporal Sequences
We investigate a form of modular neural network for classification with (a) pre-separated input vectors entering its specialist (expert) networks, (b) specialist networks which ar...
Sylvian R. Ray, William H. Hsu
IJCNN
2007
IEEE
15 years 4 months ago
Random Feature Subset Selection for Analysis of Data with Missing Features
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Joseph DePasquale, Robi Polikar