Deep Learning for Plant Phenotyping

Mori, Matteo (2016) Deep Learning for Plant Phenotyping. [Dissertation (University of Nottingham only)]

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Abstract

Plant Phenotyping is an emerging science which provides us the knowledge to better understand plants. Indeed, the study of the link between genetic background and environment in which plants develop can help us to determine cures for plants’ sicknesses and new ways to improve yields using limited resources. In this regard, one of the main aspects of Plant Phenotyping that were studied in the past, was Root Phenotyping, which is based on the study of the root architectures. In particular, today with great technology innovations, it was possible to focus the research on non-invasive approaches which allow to study the root development belowground without altering the natural plants’ environment. One of the most common practices, is to make use of X-ray microcomputed tomography (

Item Type: Dissertation (University of Nottingham only)
Keywords: Plant phenotyping, root phenotyping, roots, X-ray microcomputed tomography, uCT, Deep learning, convolutional neural networks, CNN, classification, segmentation.
Depositing User: Gonzalez-Orbegoso, Mrs Carolina
Date Deposited: 18 Jan 2017 12:21
Last Modified: 19 Jan 2017 18:05
URI: http://eprints.nottingham.ac.uk/id/eprint/39172

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