Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Engineering Applications of Artificial Intelligence
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We consider the problem of the reconstruction of spectral reflectance curves from multispectral images by using non-linear methods. In the search for a reconstruction method able to provide noise resistance and good generalization we apply mixture density networks (MDN). The problem of architecture optimisation of the MDN is solved by using random sampling and genetic algorithms. This approach has been tested and compared with a linear method already used for spectral reconstruction of fine art paintings. This has been done using simulated and real data. MDN-based methods provide good results in both cases. In particular, the results obtained on real experimental data clearly show the superiority of the MDN-based approach over the linear one taken as reference.