2024
DOI: 10.1016/j.compag.2024.108620
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Occlusion-aware fruit segmentation in complex natural environments under shape prior

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Cited by 9 publications
(2 citation statements)
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“…Among the key enabling technologies for automated harvesting are visual algorithms, which have attracted growing research attention. Traditional machine vision methods often rely on manually extracted features such as texture, color, and shape for visual inspection [ 2 , 3 , 4 ]. However, these approaches are limited by human cognition, extracting insufficient features in complex orchard environments.…”
Section: Introductionmentioning
confidence: 99%
“…Among the key enabling technologies for automated harvesting are visual algorithms, which have attracted growing research attention. Traditional machine vision methods often rely on manually extracted features such as texture, color, and shape for visual inspection [ 2 , 3 , 4 ]. However, these approaches are limited by human cognition, extracting insufficient features in complex orchard environments.…”
Section: Introductionmentioning
confidence: 99%
“…Fully hidden fruits, enclosed by leaves, are not detectable from any angle, whereas partially obscured fruits can be seen better from specific angles. (Liang et al, 2024) proposed adding spherical shapes prior to detection, while (T. suggested a 3D fruit localisation method that determines centroid coordinates and approximates shape.…”
Section: Introductionmentioning
confidence: 99%