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ICRA
2007
IEEE
117views Robotics» more  ICRA 2007»
13 years 11 months ago
Predicting Object Dynamics from Visual Images through Active Sensing Experiences
Prediction of dynamic features is an important task for determining the manipulation strategies of an object. This paper presents a technique for predicting dynamics of objects re...
Shun Nishide, Tetsuya Ogata, Jun Tani, Kazunori Ko...
ICNSC
2007
IEEE
13 years 11 months ago
Associative Memory for Noisy and Structurally Deformed Two-Dimensional Images Using Neural Networks
—This paper studies the problem of understanding noisy and structurally deformed two-dimensional images by means of abstractly defined neural works. First, in the framework of sy...
Hiroshi Inaba, Tomoki Takahashi, Keylan Alimhan
CEC
2007
IEEE
13 years 11 months ago
NEMO: neural enhancement for multiobjective optimization
— In this paper, a neural network approach is presented to expand the Pareto-optimal front for multiobjective optimization problems. The network is trained using results obtained...
Aaron Garrett, Gerry V. Dozier, Kalyanmoy Deb
AVSS
2007
IEEE
13 years 11 months ago
Face localization by neural networks trained with Zernike moments and Eigenfaces feature vectors. A comparison
Face localization using neural network is presented in this communication. Neural network was trained with two different kinds of feature parameters vectors; Zernike moments and E...
Mohammed Saaidia, Anis Chaari, Sylvie Lelandais, V...
SBACPAD
2008
IEEE
249views Hardware» more  SBACPAD 2008»
13 years 11 months ago
Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture
This work presents an implementation of Neocognitron Neural Network, using a high performance computing architecture based on GPU (Graphics Processing Unit). Neocognitron is an ar...
Gustavo Poli, José Hiroki Saito, Joã...
IJCNN
2008
IEEE
13 years 11 months ago
A neural network approach to ordinal regression
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
Jianlin Cheng, Zheng Wang, Gianluca Pollastri
IJCNN
2008
IEEE
13 years 11 months ago
Evolving a neural network using dyadic connections
—Since machine learning has become a tool to make more efficient design of sophisticated systems, we present in this paper a novel methodology to create powerful neural network ...
Andreas Huemer, Mario A. Góngora, David A. ...
IJCNN
2008
IEEE
13 years 11 months ago
Airport noise simulation using neural networks
— Aircraft noise is influenced by many complex factors and it is difficult to devise an accurate mathematical model to simulate it with respect to operations at an airport. Thi...
Yingjie Yang, Chris J. Hinde, David Gillingwater
IJCNN
2008
IEEE
13 years 11 months ago
Wafer-scale integration of analog neural networks
Abstract— This paper introduces a novel design of an artificial neural network tailored for wafer-scale integration. The presented VLSI implementation includes continuous-time a...
Johannes Schemmel, Johannes Fieres, Karlheinz Meie...
ICTAI
2008
IEEE
13 years 11 months ago
The Performance of Approximating Ordinary Differential Equations by Neural Nets
—The dynamics of many systems are described by ordinary differential equations (ODE). Solving ODEs with standard methods (i.e. numerical integration) needs a high amount of compu...
Josef Fojdl, Rüdiger W. Brause