TITLE: Automatic Dataset Builder for Machine Learning Applications to Satellite Imagery 

ABSTRACT: Nowadays the use of Machine Learning (ML) algorithms is spreading in the
field of Remote Sensing, with applications ranging from detection and
classification of land use and monitoring to the prediction of many natural or
anthropic phenomena of interest. One main limit of their employment is related
to the need for a huge amount of data for training the neural network, chosen
for the specific application, and the resulting computational weight and time
required to collect the necessary data. In this letter the architecture of an
innovative tool, enabling researchers to create in an automatic way suitable
datasets for AI (Artificial Intelligence) applications in the EO (Earth
Observation) context, is presented. Two versions of the architecture have been
implemented and made available on Git-Hub, with a specific Graphical User
Interface (GUI) for non-expert users.
Nowadays the use of Machine Learning (ML) algorithms is spreading in the
field of Remote Sensing, with applications ranging from detection and
classification of land use and monitoring to the prediction of many natural or
anthropic phenomena of interest. One main limit of their employment is related
to the need for a huge amount of data for training the neural network, chosen
for the specific application, and the resulting computational weight and time
required to collect the necessary data. In this letter the architecture of an
innovative tool, enabling researchers to create in an automatic way suitable
datasets for AI (Artificial Intelligence) applications in the EO (Earth
Observation) context, is presented. Two versions of the architecture have been
implemented and made available on Git-Hub, with a specific Graphical User
Interface (GUI) for non-expert users.
Automatic Dataset Builder for Machine Learning Applications to Satellite Imagery
http://arxiv.org/abs/2008.01578v1