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» Probabilistic Neural Network Models for Sequential Data
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ICCV
1998
IEEE
14 years 10 months ago
Visual Motion Estimation and Prediction: A Probabilistic Network Model for Temporal Coherence
We develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to p...
Alan L. Yuille, Pierre-Yves Burgi, Norberto M. Grz...
ICANN
2005
Springer
14 years 1 months ago
Robust Structural Modeling and Outlier Detection with GMDH-Type Polynomial Neural Networks
Abstract. The paper presents a new version of a GMDH type algorithm able to perform an automatic model structure synthesis, robust model parameter estimation and model validation i...
Tatyana I. Aksenova, Vladimir Volkovich, Alessandr...
NIPS
2000
13 years 9 months ago
Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics
Experimental data show that biological synapses behave quite differently from the symbolic synapses in common artificial neural network models. Biological synapses are dynamic, i....
Thomas Natschläger, Wolfgang Maass, Eduardo D...
INFORMATICALT
2000
118views more  INFORMATICALT 2000»
13 years 8 months ago
Hexagonal Approach and Modeling for the Visual Cortex
In this paper, the hexagonal approach was proposed for modeling the functioning of cerebral cortex, especially, the processes of learning and recognition of visual information. Thi...
Algis Garliauskas, Alvydas Soliunas
CORR
2010
Springer
169views Education» more  CORR 2010»
13 years 8 months ago
Spiking Neurons with ASNN Based-Methods for the Neural Block Cipher
Problem statement: This paper examines Artificial Spiking Neural Network (ASNN) which inter-connects group of artificial neurons that uses a mathematical model with the aid of blo...
Saleh Ali K. Al-Omari, Putra Sumari