Global Optimization versus Deterministic Pruning for the Classification of Remotely Sensed Imagery
The effect of pruning neural network structures in remote sensing is investigated. Standard pruning methods, i.e., Optimal Brain Damage and Optimal Brain Surgeon, are compared with pruning based on a genetic algorithm. Direct coding is used to represent the links of the network for optimization with a canonical genetic algorithm using binary representation. The results show that the genetic algorithm
is the only method able to discover a significantly better neural network structure. The main drawback of the genetic approach is the extensive training time required.
STATHAKIS Dimitrios;
KANELLOPOULOS Ioannis;
2008-11-11
AMER SOC PHOTOGRAMMETRY
JRC47194
0099-1112,
https://publications.jrc.ec.europa.eu/repository/handle/JRC47194,
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