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Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks.

, , , , and . Remote. Sens., 11 (11): 1309 (2019)

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Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks., , , , and . Remote. Sens., 11 (11): 1309 (2019)Multisensor Data Fusion for Improved Segmentation of Individual Tree Crowns in Dense Tropical Forests., , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2021)Injecting Domain Knowledge Into Deep Neural Networks for Tree Crown Delineation., , , , , , , , and . IEEE Trans. Geosci. Remote. Sens., (2022)Improving Rare Tree Species Classification Using Domain Knowledge., , , , , , and . IEEE Geosci. Remote. Sens. Lett., (2023)A benchmark dataset for canopy crown detection and delineation in co-registered airborne RGB, LiDAR and hyperspectral imagery from the National Ecological Observation Network., , , , , , , and . PLoS Comput. Biol., (2021)Addressing Annotation Imprecision for Tree Crown Delineation Using the RandCrowns Index., , , , , , , and . CoRR, (2021)A superstructure-based design of experiments framework for simultaneous domain-restricted model identification and parameter estimation., , , , , and . Comput. Chem. Eng., (2017)RandCrowns: A Quantitative Metric for Imprecisely Labeled Tree Crown Delineation., , , , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2021)Cross-site learning in deep learning RGB tree crown detection., , , , and . Ecol. Informatics, (2020)