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Deep phenotyping: Deep learning for temporal phenotype/genotype classification

Taghavi Namin, Sarah; Esmaeilzadeh, Mohammad; Najafi, Mohammad; Brown, Timothy; Borevitz, Justin

Description

Background High resolution and high throughput genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks and Long-Short Term Memories (LSTMs), have shown great success in visual data recognition, classification, and sequence learning tasks. More recently, CNNs have been used for plant classification and phenotyping, using...[Show more]

CollectionsANU Research Publications
Date published: 2018
Type: Journal article
URI: http://hdl.handle.net/1885/157386
Source: Plant Methods
DOI: 10.1186/s13007-018-0333-4
Access Rights: Open Access

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