[P] 33 Imaging/Quantification

[PO-716] Deep Learning-based Recognition of Arabidopsis Accessions using Time-Series RGB High-Throughput Measurements

[on-site]

*Rijad Saric^1,2,3, Amila Akagic⁴, Edhem Custovic^2,3, Oliver Berkowitz^1,2, Mathew G. Lewsey^1,2, James Whelan^1,2,5 (1. La Trobe Institute for Sustainable Agriculture & Food (LISAF), Department of Animal, Plant and Soil Sciences, La Trobe University, VIC 3086, Australia., 2. Australian Research Council Research Hub for Medicinal Agriculture, AgriBio Building, La Trobe University, Bundoora, VIC 3086, Australia , 3. Department of Engineering, School of Computing, Engineering and Mathematical Sciences, La Trobe University, Bundoora, VIC 3086, Australia , 4. Faculty of Electrical Engineering, University of Sarajevo, 71000 Sarajevo, Bosnia and Herzegovina, 5. College of Life Sciences, Zhejiang University, Hangzhou, 310027, China)

Keywords:Imaging/quantification, Mathematics/modeling, Database/software/bioinformatics