Copyright © Mon Nov 2 21:39:53 2009
by Michael Ley (firstname.lastname@example.org)
- Ayanna M. Howard, Curtis Padgett:
An adaptive learning methodology for intelligent object detection in novel imagery data.
- Algis Garliauskas:
Self-organized topological structures in neural networks for the visual cortex of the brain.
- Kaibo Duan, S. Sathiya Keerthi, Aun Neow Poo:
Evaluation of simple performance measures for tuning SVM hyperparameters.
- Stefania Gentili:
A new method for information update in supervised neural structures.
- Ajantha S. Atukorale, Tom Downs, Ponnuthurai N. Suganthan:
Boosting the HONG network.
- Da Deng, Nikola K. Kasabov:
On-line pattern analysis by evolving self-organizing maps.
- Tong Zhao, Lilian H. Y. Tang, Horace Ho-Shing Ip, Feihu Qi:
On relevance feedback and similarity measure for image retrieval with synergetic neural nets.
- Jayanta Basak, Anirban Das:
Hough transform network: a class of networks for identifying parametric structures.
- Francesco Camastra, Alessandro Vinciarelli:
Combining neural gas and learning vector quantization for cursive character recognition.
- Kunihiko Fukushima:
Neocognitron for handwritten digit recognition.
- Takio Kurita, Takashi Takahashi:
Viewpoint independent face recognition by competition of the viewpoint dependent classifiers.
- Lin-Lin Huang, Akinobu Shimizu, Yoshihiro Hagihara, Hidefumi Kobatake:
Face detection from cluttered images using a polynomial neural network.
- Noriko Yoshiike, Yoshiyasu Takefuji:
Object segmentation using maximum neural networks for the gesture recognition system.
- Najet Arous, Noureddine Ellouze:
Cooperative supervised and unsupervised learning algorithm for phoneme recognition in continuous speech and speaker-independent context.
- Yas Abbas Alsultanny, Musbah M. Aqel:
Pattern recognition using multilayer neural-genetic algorithm.
- Chunrong Yuan, Heinrich Niemann:
Neural networks for appearance-based 3-D object recognition.
- Friedhelm Schwenker, Christian Dietrich, Hans A. Kestler, Helge Klaus Rieder, Günther Palm:
Radial basis function neural networks and temporal fusion for the classification of bioacoustic time series.
- Lei Xu:
BYY learning, regularized implementation, and model selection on modular networks with one hidden layer of binary units.
- Yolanda Blanco Archilla, Santiago Zazo:
New Gaussianity measures based on order statistics: application to ICA.
- Lijuan Cao:
Support vector machines experts for time series forecasting.
- Xu Han, Dao-Lin Xu, Gui-Rong Liu:
A computational inverse technique for material characterization of a functionally graded cylinder using a progressive neural network.
- Liying Ma, Khashayar Khorasani:
A new strategy for adaptively constructing multilayer feedforward neural networks.
- Jane Weizhen Lu, H. Y. Fan, S. M. Lo:
Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong.
- Rubin Wang, Zhikang Zhang, Yun-Bo Duan:
Nonlinear stochastic models of neurons activities.
- An-Chyau Huang:
Model reference adaptive control of a class of non-autonomous systems using serial input neuron.
- Rong-Jong Wai:
Tracking control based on neural network strategy for robot manipulator.
- Donald L. Hung, Jun Wang:
Digital hardware realization of a recurrent neural network for solving the assignment problem.
- H. John Caulfield:
- Marcelo Azevedo Costa, Antônio de Pádua Braga, Benjamin Rodrigues de Menezes, Roselito de Albuquerque Teixeira, Gustavo Guimarães Parma:
Training neural networks with a multi-objective sliding mode control algorithm.
- Chunguang Li, Hongbing Xu, Xiaofeng Liao, Juebang Yu:
Tabu search for CNN template learning.
- Han-joon Kim, Sang-goo Lee:
Building topic hierarchy based on fuzzy relations.
- Raul Cristian Muresan:
Pattern recognition using pulse-coupled neural networks and discrete Fourier transforms.
- Ayca Kumluca Topalli, Ismet Erkmen:
A hybrid learning for neural networks applied to short term load forecasting.
- Haralambos Sarimveis, Alex Alexandridis, George V. Bafas:
A fast training algorithm for RBF networks based on subtractive clustering.