@inproceedings{230f29e7b2be4bb098c46f46500dcdd2,
title = "Monitoring Leafy Plant Root Morphology with Pattern Recognition Imaging Techniques",
abstract = "Root morphology is an accurate indicator of plant health and nutrition. This study uses YOLOv3 to monitor leafy plant roots and image processing to assess their growth and nutrition. We partnered with an indoor agriculture company called Greenscale, who wanted an automated approach to monitoring the root health of their plants. This study processes the raw images obtained from Greenscale using several image processing tools and techniques and then trains the YOLO v3 model. Based on several performance metrics, the model has been found to be highly effective in accurately delineating various stages of root growth.",
keywords = "CNN, deep learning, object detection, root morphology, YOLO",
author = "Peyal, \{Md Mahmudul Kabir\} and Shihab, \{Ashraf Ul Islam\} and Ocean, \{S. I.\} and Nafiu Nawar and Hao Chen",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025 ; Conference date: 06-01-2025 Through 08-01-2025",
year = "2025",
doi = "10.1109/CCWC62904.2025.10903707",
language = "English",
series = "2025 IEEE 15th Annual Computing and Communication Workshop and Conference, CCWC 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "666--671",
editor = "Rajashree Paul and Arpita Kundu",
booktitle = "2025 IEEE 15th Annual Computing and Communication Workshop and Conference, CCWC 2025",
address = "United States",
}