The dataset comprises data from two cities, intended for evaluating the pretraining and transfer-learning capabilities of the GitHub repository stark-t/UncertaintySlumDetection (github.com). Each city
Abstract: The objective of this work was to propose a new methodology for mapping coffee cropping areas that includes multitemporal data as input parameters in the classification process, by using the
Imágenes satelitales para cuatro volcanes de Chile: Complejo Volcánico Nevados de Chillán, Complejo Volcánico Taapaca, Volcán Parinacota y Volcán Villarrica.
