Wheat Yield Assessment Using In-Field Organ-Scale Phenotyping and Deep Learning Methods

Carlier, Alexis

Download

Doctoral thesis (Dissertations and theses)

Wheat Yield Assessment Using In-Field Organ-Scale Phenotyping and Deep Learning Methods

Carlier, Alexis

2023

Permalink
https://hdl.handle.net/2268/306283

Files (1)Send to Details Statistics Bibliography Similar publications

Files

Full Text

Alexis Carlier Thèse.pdf

Author postprint (91.14 MB)

Download

All documents in ORBi are protected by a user license.

Send to

RIS BibTex APA Chicago Permalink X Linkedin

Details

Keywords :

phenotyping; wheat; AI

Disciplines :

Agriculture & agronomy

Author, co-author :

Carlier, Alexis ; Université de Liège - ULiège > TERRA Research Centre > Biosystems Dynamics and Exchanges (BIODYNE)

Language :

English

Title :

Wheat Yield Assessment Using In-Field Organ-Scale Phenotyping and Deep Learning Methods

Defense date :

14 September 2023

Institution :

ULiège. GxABT - Liège Université. Gembloux Agro-Bio Tech [BE], Belgium

Degree :

Doctorat en sciences agronomiques et ingénierie biologique

Promotor :

Mercatoris, Benoît ; Université de Liège - ULiège > TERRA Research Centre > Biosystems Dynamics and Exchanges (BIODYNE)

Dumont, Benjamin ; Université de Liège - ULiège > TERRA Research Centre > Plant Sciences

President :

Lejeune, Philippe ; Université de Liège - ULiège > TERRA Research Centre > Gestion des ressources forestières

Jury member :

Leemans, Vincent ; Université de Liège - ULiège > Département GxABT > Biosystems Dynamics and Exchanges (BIODYNE)

Rousseau David; UA - Université d'Angers [FR]

Mouazen Abdul; UGent - Ghent University [BE]

Baeten Vincent; CRA-W - Centre Wallon de Recherches agronomiques [BE]

Name of the research project :

Phenwheat

Available on ORBi :

since 06 September 2023

Statistics

Number of views

132 (19 by ULiège)

Number of downloads

72 (12 by ULiège)

More statistics