Joan Vila-Francés

TL;DR: This framework of composite kernels demonstrates enhanced classification accuracy as compared to traditional approaches that take into account the spectral information only, flexibility to balance between the spatial and spectral information in the classifier, and computational efficiency.

TL;DR: This letter presents a modification to the established Fraunhofer line discrimination method for improving the accuracy of the solar-induced chlorophyll fluorescence retrieval over terrestrial vegetation by introducing two correction coefficients that relate the values of the fluorescence and the reflectance inside and outside the absorption band.

TL;DR: A Bayesian approach to ELM is proposed, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap; and presents high generalization capabilities.

TL;DR: Results suggest that RVMs offer an excellent trade-off between accuracy and sparsity of the solution, and become less sensitive to the selection of the free parameters.

TL;DR: In this article, the authors used Artificial Neural Networks (ANNs) to predict ozone levels in a small town near Valencia (Spain) in three different time windows: all the time of study (April of 1997, 1999 and 2000), one month (April 1999), and finally, an hourly analysis.