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IJCNN
2006
IEEE
8 years 10 months ago
Language Acquisition and Symbol Grounding Transfer with Neural Networks and Cognitive Robots
— Neural networks have been proposed as an ideal cognitive modeling methodology to deal with the symbol grounding problem. More recently, such neural network approaches have been...
Angelo Cangelosi, Emmanouil Hourdakis, Vadim Tikha...
IJCNN
2006
IEEE
8 years 10 months ago
An Exhaustive Search Strategy for Detecting Persons in Beach Scenes using Digital Video Imagery and Neural Network-based Classif
Abstract— This paper presents an investigation of a neuralbased technique for detecting and quantifying persons in beach imagery for the purpose of predicting trends of tourist a...
Steve Green, Michael Blumenstein
IJCNN
2006
IEEE
8 years 10 months ago
Predicting Juvenile Diabetes from Clinical Test Results
—Two approaches to building models for prediction of the onset of Type 1 diabetes mellitus in juvenile subjects were examined. A set of tests performed immediately before diagnos...
Shibendra S. Pobi, Lawrence O. Hall
IJCNN
2006
IEEE
8 years 10 months ago
A Mobile Vision System with Reconfigurable Intelligent Agents
— Performing face detection and tracking on a mobile robot in a dynamic environment is a challenging task with the real-time constraints. To realize a natural reactive behavior o...
Yan Meng
IJCNN
2006
IEEE
8 years 10 months ago
In-Place Learning for Positional and Scale Invariance
— In-place learning is a biologically inspired concept, meaning that the computational network is responsible for its own learning. With in-place learning, there is no need for a...
Juyang Weng, Hong Lu, Tianyu Luwang, Xiangyang Xue
IJCNN
2006
IEEE
8 years 10 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
IJCNN
2006
IEEE
8 years 10 months ago
Cellular SRN Trained by Extended Kalman Filter Shows Promise for ADP
— Cellular simultaneous recurrent neural network has been suggested to be a function approximator more powerful than the MLP’s, in particular for solving approximate dynamic pr...
Roman Ilin, Robert Kozma, Paul J. Werbos
IJCNN
2006
IEEE
8 years 10 months ago
Nonlinear principal component analysis of noisy data
With very noisy data, having plentiful samples eliminates overfitting in nonlinear regression, but not in nonlinear principal component analysis (NLPCA). To overcome this problem...
William W. Hsieh
IJCNN
2006
IEEE
8 years 10 months ago
A Variational EM Approach to Predicting Uncertainty in Supervised Learning
— In many applications of supervised learning, the conditional average of the target variables is not sufficient for prediction. The dependencies between the explanatory variabl...
Markus Harva
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