Files in this item



application/pdfSP21-ECE499-Thesis-Li, Ruohua.pdf (2MB)Restricted to U of Illinois
(no description provided)PDF


Title:Plant segmentation using machine learning methods with low data reliance
Author(s):Li, Ruohua
Contributor(s):Narendra, Ahuja
Degree:B.S. (bachelor's)
Subject(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.
Issue Date:2021-05
Genre:Dissertation / Thesis
Date Available in IDEALS:2021-08-25

This item appears in the following Collection(s)

Item Statistics