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FCRN-BASED MULTI-TASK LEARNING FOR AUTOMATIC CITRUS TREE DETECTION FROM UAV IMAGES
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Abstract. Citrus producers need to monitor orchards frequently, and would benefit greatly from having automated tools to analyze aerial images acquired by drones over the plantations. However, analysing large aerial data sets to enable producers to take management decisions that would optimize productivity and sustainability over time and space remains challenging. Motivated by the success of deep learning in computer vision, this work proposes a novel approach based on Fully Convolutionaldoi:10.5194/isprs-annals-iv-3-w2-2020-65-2020 fatcat:louaepd3gzb4ript44prpltr7i