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IJCNN
2007
IEEE
16 years 1 months ago
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks
— A single biological neuron is able to perform complex computations that are highly nonlinear in nature, adaptive, and superior to the perceptron model. A neuron is essentially ...
Manish Saggar, Tekin Meriçli, Sari Andoni, ...
164
Voted
PKDD
2007
Springer
91views Data Mining» more  PKDD 2007»
16 years 1 months ago
Domain Adaptation of Conditional Probability Models Via Feature Subsetting
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
Sandeepkumar Satpal, Sunita Sarawagi
CSB
2005
IEEE
166views Bioinformatics» more  CSB 2005»
16 years 28 days ago
Artificial Neural Networks to Predict Daylily Hybrids
Artificial Neural Networks (ANN) were employed to predict daylily (Hemerocalli spp.) hybrids from known characteristics of parents used in hybridization. Features such as height, ...
Ramana M. Gosukonda, Masoud Naghedolfeizi, Johnny ...
IS4TH
2003
Springer
16 years 15 days ago
Integrating Geometric and Biomechanical Models of a Liver Tumour for Cryosurgery Simulation
Abstract. In this paper, we present a 3D reconstruction approach of a liver tumour model from a sequence of 2D MR parallel cross-sections, and the integration of this reconstructed...
Alexandra Branzan Albu, Jean-Marc Schwartz, Denis ...
230
Voted
CVPR
2010
IEEE
15 years 5 months ago
Multi-structure model selection via kernel optimisation
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Tat-Jun Chin, David Suter, Hanzi Wang