Plant segmentation using machine learning methods with low data reliance
Li, Ruohua
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Permalink
https://hdl.handle.net/2142/110355
Description
Title
Plant segmentation using machine learning methods with low data reliance
Author(s)
Li, Ruohua
Contributor(s)
Narendra, Ahuja
Issue Date
2021-05
Keyword(s)
Computer Vision
Plant Phenotyping
Image Segmentation
Semantic Segmentation
Abstract
This thesis examines the potential of some learning-based computer vision algorithms with low data
reliance on the problem of plant segmentation, namely, few-shot learning algorithms and clustering
algorithm. We thoroughly investigate the mechanisms, benchmarks, and features of each algorithm.
Each algorithm is applied to the plant segmentation problem. Then we show and discuss the results
of each algorithm and further apply possible modifications and tuning to them. After this study, we
have gathered performances for three different algorithms which have recall values of 54.8%, 87.7%,
and 96.9% respectively.
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