José M. Peña

TL;DR: This paper proposes a method called Mlnb which adapts the traditional naive Bayes classifiers to deal with multi-label instances and achieves comparable performance to other well-established multi- label learning algorithms.

TL;DR: A systematic evaluation of several autofocus functions used for analytical fluorescent image cytometry studies of counterstained nuclei shows that functions based on correlation measures have the best performance for this type of image.

TL;DR: In this article, a UAV equipped with a commercial camera (visible spectrum) was used for ultra-high resolution image acquisition over a wheat field in the early-season period, and six visible spectral indices (CIVE, ExG, ExGR, Woebbecke Index, NGRDI, VEG) and two combinations of these indices were calculated and evaluated for vegetation fraction mapping, to study the influence of flight altitude (30 and 60m) and days after sowing (DAS) from 35 to 75 DAS on the classification accuracy.

TL;DR: A robust and innovative automatic object-based image analysis (OBIA) algorithm was developed on Unmanned Aerial Vehicle images to design early post-emergence prescription maps, which could help farmers in decision-making to optimize crop management by rationalization of the herbicide application.

TL;DR: An innovative procedure for computing the 3-dimensional geometric features of individual trees and tree-rows by applying two consecutive phases: generation of Digital Surface Models with Unmanned Aerial Vehicle (UAV) technology and use of object-based image analysis techniques.